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Assessing urban sidewalk networks based on three constructs: a synthesis of pedestrian level of service literature

December 2019
Transport Reviews

December 2019

DOI:10.1080/01441647.2019.1703841

Authors:

Dipanjan Nag

Norwegian University of Science and Technology

Arkopal Goswami

Indian Institute of Technology Kharagpur

Ankit Gupta

Indian Institute of Technology (Banaras Hindu University) Varanasi

Joy Sen

Indian Institute of Technology Kharagpur

Pedestrian Level of Service (PLOS) models are widely used to assess walking facilities. These models have been in existence since the 1970s, wherein the process broadly consists of three steps, i.e. attribute selection, model calibration, and classification of model results into service-level categories, based on Measures of Effectiveness (MOEs). This paper reviews existing sidewalk PLOS studies based on their association with the three constructs of flow characteristics, built environment and users’ perception, which in combination represents the entire walking environment spectrum, as has been indicated by existing researchers. Forty-seven PLOS studies, along with eight review papers, written by authors from the Americas, Europe, Asia and Australia, between the years of 1971 and 2019, are analysed in this review. The review finds that although 49% of the studies employed both qualitative and quantitative data for their respective methodologies, but none of them use all the three broad constructs in a combined fashion. Also, in selecting the attributes to be used for developing the PLOS, these studies have only referred to previous literature available at that point in time, and not employed any consistent and robust method in selecting context-specific attributes. When it came to the preferred analysis technique, 60% of the studies favoured the use of the regression technique while calibrating their model, whereas 22% used a points-based marking scheme. Finally, 89% of the studies manually classifies the PLOS model results to respective service levels (i.e. letter grades), as opposed to utilising a classification algorithm. In addition, this review could identify only one paper that describes a PLOS based on pedestrian route directness, which is a measure of pedestrian network connectivity. In view of these findings, the review paper suggests the need of a robust methodology in selection of attributes and the use of innovative modelling techniques, both of which could allow the utilisation of all three constructs. Also, such advanced modelling techniques could bypass the need for categorising service levels manually. Finally, the study advocates the use of network connectivity measures in developing sidewalk PLOS, as it is an important part of the built environment.

Interrelationships between the three broad constructs.

…

Research items as per article type and country.

…

Distribution of PLOS studies across countries and decades.

…

Review papers as per Journal and country of author(s).

…

Most utilised (a) flow characteristics; (b) built environment; (c) users' perception attribute type.

…

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Assessing urban sidewalk networks based on

three constructs: a synthesis of pedestrian level of

service literature

Dipanjan Nag, Arkopal Kishore Goswami, Ankit Gupta & Joy Sen

To cite this article: Dipanjan Nag, Arkopal Kishore Goswami, Ankit Gupta & Joy Sen (2019):

Assessing urban sidewalk networks based on three constructs: a synthesis of pedestrian level of

service literature, Transport Reviews, DOI: 10.1080/01441647.2019.1703841

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Assessing urban sidewalk networks based on three constructs:

a synthesis of pedestrian level of service literature

Dipanjan Nag

, Arkopal Kishore Goswami

, Ankit Gupta

and Joy Sen

a,c

Ranbir & Chitra Gupta School of Infrastructure Design & Management, Indian Institute of Technology

Kharagpur, Kharagpur, India;

Department of Civil Engineering, Indian Institute of Technology, Banaras Hindu

University, Varanasi, India;

Department of Architecture & Regional Planning, Indian Institute of Technology

Kharagpur, Kharagpur, India

ABSTRACT

Pedestrian Level of Service (PLOS) models are widely used to assess

walking facilities. These models have been in existence since the

1970s, wherein the process broadly consists of three steps, i.e.

attribute selection, model calibration, and classiﬁcation of model

results into service-level categories, based on Measures of

Eﬀectiveness (MOEs). This paper reviews existing sidewalk PLOS

studies based on their association with the three constructs of

ﬂow characteristics,built environment and users’perception, which

in combination represents the entire walking environment

spectrum, as has been indicated by existing researchers. Forty-

seven PLOS studies, along with eight review papers, written by

authors from the Americas, Europe, Asia and Australia, between

the years of 1971 and 2019, are analysed in this review. The

review ﬁnds that although 49% of the studies employed both

qualitative and quantitative data for their respective

methodologies, but none of them use all the three broad

constructs in a combined fashion. Also, in selecting the attributes

to be used for developing the PLOS, these studies have only

referred to previous literature available at that point in time, and

not employed any consistent and robust method in selecting

context-speciﬁc attributes. When it came to the preferred analysis

technique, 60% of the studies favoured the use of the regression

technique while calibrating their model, whereas 22% used a

points-based marking scheme. Finally, 89% of the studies

manually classiﬁes the PLOS model results to respective service

levels (i.e. letter grades), as opposed to utilising a classiﬁcation

algorithm. In addition, this review could identify only one paper

that describes a PLOS based on pedestrian route directness, which

is a measure of pedestrian network connectivity. In view of these

ﬁndings, the review paper suggests the need of a robust

methodology in selection of attributes and the use of innovative

modelling techniques, both of which could allow the utilisation of

all three constructs. Also, such advanced modelling techniques

could bypass the need for categorising service levels manually.

Finally, the study advocates the use of network connectivity

measures in developing sidewalk PLOS, as it is an important part

of the built environment.

ARTICLE HISTORY

Received 8 January 2019

Accepted 14 November 2019

KEYWORDS

Pedestrian Level of Service

(PLOS); ﬂow characteristics;

built environment; users’

perception; sidewalk network

CONTACT Dipanjan Nag el.diablo.diablo78@gmail.com

TRANSPORT REVIEWS

https://doi.org/10.1080/01441647.2019.1703841

1. Introduction

Pedestrian Level of Service (PLOS) is deﬁned by the Highway Capacity Manual (2000)as“a

qualitative measure of pedestrian traﬃcﬂow, along with environmental factors that might

aﬀect perceived level of comfort, convenience, safety, security and the economy of

walkway systems”. PLOS allows six letter grades (A–F) to be assigned to pedestrian facili-

ties under consideration, where a score “A”would mean the best PLOS, and alternately the

score of “F”means the worst. This process of categorisation to diﬀerent service levels

(letter grades) is based on certain attributes, also called measures of eﬀectiveness

(MOE). Kadali and Vedagiri (2016) consider PLOS assessment as the most reliable

method for assessing existing facilities. While using this measure it is important to under-

stand the “criteria for assessment”as deﬁned by diﬀerent researchers. These “criteria for

assessment”focus on diﬀerent aspects of the walking environment and can be grouped

under three broad constructs. Existing research and review studies on factors inﬂuencing

the entire range of the walking environment have hinted towards the following three

broad constructs (Cervero, Sarmiento, Jacoby, Gomez, & Neiman, 2009; Ewing &

Cervero, 2010; Landis, Ottenberg, Mcleod, & Guttenplan, 2001; Maghelal & Capp, 2011;

Olsen, Macdonald, & Ellaway, 2017; Singh & Jain, 2011; Vale, Saraiva, & Pereira, 2016).

.Flow characteristics of pedestrians and vehicular traﬃc

.Physical elements of built walking environment, and

.Users’perception of the walking environment

It is observed that there is a large variation in the methodology adopted in existing

PLOS studies. These diﬀerences are in terms of selection of attributes, the techniques

adopted for PLOS model calibration and ﬁnally in the classiﬁcation to service levels. There-

fore, an in-depth review of existing literature is required on these aspects which is cur-

rently not being addressed by existing review papers. Thus, the present paper

systematically reviews a comprehensive list of PLOS studies with the timeline set from

1971 (i.e. the ﬁrst PLOS conception by John J. Fruin) up till 2019 (i.e. the present), with

an intent to answer the following ﬁve questions:

.How are the attributes being selected while developing PLOS measures?

.How are these measures modelled or calibrated?

.How are the service levels deﬁned?

.Are all the constructs represented?

.Is the walking network (network attributes) taken into account?

2. PLOS concept for evaluation of the urban walking environment: the

three constructs

PLOS could be considered equivalent to any performance assessment tool, where the

eﬃciency of the tool lies in its ability to capture all the aspect of the process. For

example, in the business or marketing ﬁelds (Franceschini, Cignetti, & Caldara, 1998)a

service quality measure, considers two groups of concepts –perception & expectations.

2D. NAG ET AL.

If an analogy were to be drawn between such measures and PLOS –perception would

relate users experience of the facility, whereas expectation would encompass all the oper-

ational and built characteristics of the facility.

Perception plays an important role in an individuals’decision to use a walking facility.

Research has shown that user perception factors such as absence of comfort, convenience,

safety, and shade (Zainol, Ahmad, Nordin, & Aripin, 2014), and physical built walking

environment elements such as the presence of driveways, bus stops, and number of

vehicle lanes (Choi, Kim, Min, Lee, & Kim, 2016), reduce the level of pedestrians’satisfac-

tion, which in turn, aﬀects their decision to walk. Kim, Sohn, and Choo (2017) analysed

relationships between pedestrian traﬃc volume and various measures of the physical

built environment at the street and neighbourhood levels to show their eﬀect on ﬂow

characteristics.

Various review papers and reports have conveyed their concern regarding the ability of

existing studies to capture all the aspects of a facility evaluation process. Bloomberg and

Burden (2006) have explained about three components –sidewalk environment, ped-

estrian characteristics and ﬂow characteristics. The sidewalk environment component is

related to the physical built walking environment, the pedestrian characteristics is associ-

ated to the individual socio-economic information, behaviour, physical ability and their

expectation (users’perception), and the ﬂow characteristics is related to the pedestrian

and vehicular traﬃcﬂow characteristics. Figure 1 is closely adopted from Bloomberg

and Burden (2006) considering the three broad constructs and their interrelationships.

Singh and Jain (2011) have stated that assessment of facilities have not been inclusive

of the entire “walking environment”. Kadali and Vedagiri (2016) have advocated on the

Figure 1. Interrelationships between the three broad constructs.

TRANSPORT REVIEWS 3

creation of a combined methodology for quantitative (speed, density, etc.) and qualitative

(comfort, safety, etc.) assessments of the pedestrian facilities. Maghelal and Capp (2011)

have addressed the need for focusing on built environment attributes as they signiﬁcantly

inﬂuence walking. As such, these three constructs are central to the evaluation procedure

of pedestrian facilities and future studies should consider integrating them.

3. PLOS and walkability indices

The Online Travel Demand Management (TDM) Encyclopaedia by Victoria Transport Policy

Institute (2009)deﬁnes “walkability”as overall walking conditions in an area and these

indices takes into account a large number of considerations based on the scale of evalu-

ation. Walkability indices are assessed at a speciﬁc site, a neighbourhood level or a com-

munity level. PLOS on the other hand always evaluates a segment of the walking facility

such as, sidewalks, mid-blocks or intersections.

In contrast to the three broad constructs explained above, Vale et al. (2016) identiﬁed

walkability indices as measures which include assessment of the infrastructure, topology,

proximity, and attraction potential of a facility. It appears that the purview of walkability

indices is much broader than PLOS measures and encompasses the three broad con-

structs. Walking as a mode is much more than just transportation between origin and des-

tination, it involves a social aspect as well. Since PLOS has emanated from vehicular LOS, it

has not been able to cater to this social aspect. An example for understanding this argu-

ment is the presence of vendors on sidewalk. Street vendors are the leading cause of side-

walk encroachment in developing countries that causes user discomfort, and also a

reduction in sidewalk capacity, when viewed from a traﬃc engineering standpoint.

However, from a social engineering understanding, removal of the vendors may aﬀect

the social cohesion, interaction and therefore local economy, especially in the market

areas. Connected to this, is the observation by Jan Gehl, who suggested in his book

“Life between buildings: Using public spaces”(Campos, 2012), that built environment

designed down to the last detail, is an essential component in inﬂuencing the quality of

the walking environment. The deterioration of such quality may not decrease the

number of people walking (as it is intrinsic to human nature), but may reduce the social

cohesion and interaction.

Moreover, as presented later in this review (Table 2 and Appendix 1), none of the PLOS

studies utilised land use as an explanatory variable in their statistical modelling process.

The same has been seen to be true about connectivity of links in the pedestrian

network. Researchers (Hajrasouliha & Yin, 2015; Li & Tsukaguchi, 2005; Ozbil, Peponis, &

Stone, 2011) studying the impact of pedestrian movements due to landuse and connec-

tivity have statistically established that these attributes play a major role, which walkability

studies have always incorporated (Ewing & Cervero, 2001; Ewing, Hajrasouliha, Neckerman,

Purciel-Hill, & Greene, 2016; Park, Ewing, Sabouri, & Larsen, 2019). In addition, two review

studies on walkability indices (Maghelal & Capp, 2011; Vale et al., 2016) were examined

along with other PLOS studies, which addressed a total of 57 walkability indices. These

researchers pointed out that most walkability studies have included infrastructure

based assessment, commonly used in PLOS, as a part of their methodology.

Following these arguments, it could be suggested that PLOS studies measure fewer

aspects of the walking environment in comparison to walkability studies. However, we

4D. NAG ET AL.

see that PLOS are still being widely used in engineering assessments. Also, Vale et al.,

2016 have argued that the number of methodologies to measure walkability is as

varied as the number of researchers creating them. Hence, to compare the relationship

between vast number of walkability indices and PLOS measures is a topic for a diﬀerent

review.

4. Methodology

The review identiﬁes PLOS studies written in English, using the electronic databases (e-

databases) and research tools. Over 500 research items (journal article, conference pro-

ceedings, relevant reports, manuals and guidelines) including many duplicates were

initially obtained in the preliminary search. PLOS for diﬀerent pedestrian facilities

were found, such as sidewalks, crosswalks, mid-block crossings, etc. Only peer-reviewed

journal papers, indexed conference proceedings and relevant technical documents (i.e.

grey literature) were considered. This paper focuses on reviewing literature on PLOS

assessment of only sidewalks (link level assessment), inclusive of the papers that docu-

ments “network-wide”sidewalk PLOS in the existing body of research. E-database

searches using the keyword “network-wide pedestrian level of service”returned only

one research paper (Stangl, 2012) related to the PLOS concept. It has been seen that

network-wide pedestrian facility assessments generally relates to connectivity indices

like Pedestrian Route Directness, Link-to-Node Ratio, etc. (Dill, 2004; Tal & Handy,

2012) and not to the PLOS concept, as was done by Stangl (2012). Finally, 46 research

items related to PLOS of sidewalks (links) and 1 PLOS study using network connectivity

measures were taken forward for full paper review and critical discussions. Studies were

also reviewed for their association with the three broad constructs and their primary

methodology for development.

Eight other review papers, six from the PLOS domain and two from the walkability

indices’arena were also included in this review. Thus in total, 55 studies were part of

this review. This paper builds upon the most current review paper by Raad and Burke

(2018), which considered 58 PLOS studies (including sidewalks and crosswalks). In this

review, 27 out of the 58 studies were included, as they focussed on sidewalks. An

additional 20 studies, which were not a part of the Raad and Burke (2018) review paper,

were included in this paper.

5. Findings from the review

The ﬁndings are grouped under ﬁve distinct sections –(i) overview of all 55 studies (47

PLOS studies and 8 review papers); (ii) attributes that are repeatedly used; (iii) broad con-

structs involved; (iv) analysis techniques and service level categorisation in the 47 PLOS

studies. In addition, an attempt is made to highlight the diﬀerences between studies orig-

inating from the developed versus developing economies.

5.1. Overview of studies

Four out of 47 (9%) PLOS studies are technical documents, 6 (13%) are conference pro-

ceedings from eminent conferences in India and around the world, and the remaining

TRANSPORT REVIEWS 5

37 (78%) are peer-reviewed journals articles in the CiteScore range of 0.1 to 3.67. Referring

to Figure 2, it is seen that majority of the work on this topic had been produced by India

(13 out of 47) and USA (12 out of 47).

This review includes recent studies (i.e. within the last two years, 2017–2019). Overall,

9 out of 47 studies (20%) are within this year range. Percentage of studies in the other

year ranges are –58% in 2010–2019, 24% in 2000–2009, 8% in 1990–1999, 8% in

1980–1989 and 2% in 1970–1979. Figure 3 suggests that there is a shift in PLOS

studies from the developed to the developing economies. The classiﬁcation of econom-

iesisasperInternationalMonetaryFund(2018) standards. There is an increase in PLOS

Figure 2. Research items as per article type and country.

Figure 3. Distribution of PLOS studies across countries and decades.

6D. NAG ET AL.

studies in developing countries in the last decade (i.e. 2010–2019), which suggests a

rising awareness of walking as a sustainable mode of transport and the importance con-

ferred on evaluating walking environments for planning improvements. Such a trend is

only natural as the previous four decades has had a large number of studies from devel-

oped economies.

Twenty-three out of 47 studies (49%) used combined qualitative and quantitative

data for their respective methodology, in comparison to studies using only quantitative

(31%) or only qualitative (20%) data. In terms of data collection methods, most studies

used multiple techniques, including videography which was found to be widely used

for collecting ﬂow parameters (24 studies), followed by response collection from individ-

uals (21 studies). The response collection process was further carried out in two ways –

response collection using questionnaire on site (17 out of 21) and response collection by

showing video clips of pedestrian facilities to the respondents (4 out of 21). Other tech-

niques used by the studies were visual assessments (7 studies) by the researchers and

physical environment audits (16 studies) that collects more detailed measurements of

features.

All eight review papers examined were articles from peer-reviewed journals in the Cite-

Score range of 0.2 to 2.05. Six out of eight review papers are speciﬁc to PLOS studies

whereas the remaining two are reviews related to walkability tools. Figure 4 shows

that India (3 out of 8) and USA (2 out of 8) has produced the most number of PLOS

review studies. Three out of the six reviews concluded that most existing studies do not

include disabled pedestrians in their consideration. Two out of the six studies converged

to the understanding that existing methods of PLOS were not capturing the entire spec-

trum of walking and therefore innovative approaches should be employed to capture the

complete walking experience.

The ﬁndings of the 47 PLOS studies and the 8 review papers are presented in Table 1,2

(excerpt of Appendix 1) and 3(excerpt of Appendix 2). For the complete details please

refer to Appendices 1 and 2.

Figure 4. Review papers as per Journal and country of author(s).

TRANSPORT REVIEWS 7

Table 1. Summary of the existing review papers studied.

Review Papers

Country of

author(s) Journal Topic

Year

range

Number of

studies Major conclusions

Sisiopiku, Byrd, and

Chittoor (2007)

USA Transportation Research

Record

Sidewalk PLOS 2000

2006

5.HCM (2000) often over estimates sidewalk LOS

.No methods consider quantitative and qualitative aspects in suﬃcient

details

Maghelal and Capp

(2011)

USA Journal of Urban and

Regional Information

Systems Association

Walkability indices 1994

2008

25 .Built environment variables are central in pedestrian studies

.Attributes of indices were classiﬁed into objective,subjective and

distinctive

Singh and Jain (2011) India Journal of Engineering

Research and Studies

Sidewalk PLOS 1996

2007

9.No methodology could be universally applied as they do not capture the

entire walking spectrum

.Methods should not be data driven

Asadi-Shekari,

Moeinaddini, and

Zaly Shah (2013)

Malaysia Transport Reviews Sidewalk PLOS 1971

2011

17 .Lack of studies considering disabled pedestrians

.Diﬃcult to link evaluation methods to design processes

.Non-applicability to all hierarchy of streets

Gupta and Pundir

(2015)

India Transport Reviews Pedestrian ﬂow

characteristics (as a

part of PLOS)

1971

2013

18 .Early PLOS studies used ﬂow characteristics as attributes

.Disabled pedestrians not considered

.Flow characteristics varies with diﬀerent context and culture

Kadali and Vedagiri

(2016)

India Transportation Research

Record

PLOS of sidewalks and

crosswalks

1971

2014

42 .Need to consider disabled pedestrians under mixed traﬃc conditions

.Need to consider Landuse in assessment process

.Need to use advanced modelling techniques

Vale et al. (2016) Portugal Journal of Transport and

Land Use

Walkability indices 1997

2013

32 .PLOS studies are classiﬁed under infrastructure based accessibility

measure

.Myriad of indices with varying methodology

Raad and Burke

(2018)

Australia Transportation Research

Record

PLOS of sidewalks and

crosswalks

1971

2016

58 .Disabled pedestrians not considered

.Need to consider Landuse in assessment process

.Connectivity is not considered

8D. NAG ET AL.

Table 2. Modelling information for PLOS studies reviewed (excerpt from Appendix 1).

Research items

Attribute

selection

technique

Modelling speciﬁcations

Analysis method

No. of locations/

sample size/

observations

Goodness of

ﬁt/validation

measureDependent attribute Independent attributes

Broad construct/s involved: ﬂow characteristics

Kim, Choi, Kim, and Tay

(2014)

CEL Evasive movements Eﬀective width, volume, landuse characters MLR 28 locations; 468

video samples of 5

mins each

= 0.77 Validated with

perceived PLOS of 216

users

Sahani and Bhuyan

(2015)

CEL Flow rate, space, speed

and V/C ratio

Eﬀective width of sidewalk HCM (2000) methodology

and Self Organising

Maps (SOM) using

Analytical Neural

Network (ANN)

NR Silhouette, Davies-Bouldin,

Clinski-Harabasz and

Dunn Index

Raghuwanshi and Tare

(2016)

CEL Average pedestrian

space

V/C ratio of pedestrians, vehicles, pedestrian

crossing time, and parking factors

MLR 9 street sections NR

Sahani and Bhuyan

(2017)

CEL Flow rate, space, speed

and V/C ratio

Eﬀective width of sidewalk HCM (2000) methodology

and three clustering

algorithms –Aﬃnity

Propagation, SOM in

ANN and Genetic

Algorithm (GA)

3764 pedestrians

observed

Clusters validated using a

number of index –

Silhouette, Davies-

Bouldin, Clinski-Harabasz

and Dunn

Cepolina, Menichini, and

Gonzalez Rojas (2018)

CEL Perceived comfort Interpersonal distances Local density method,

Voronoi diagram

395 pedestrians Validated in comparison

with HCM (2000)

Broad construct/s involved: built environment

Shekari and Zaly Shah

(2011)

Citing from 20

design

guidelines

from

developed

nations

NA Traﬃc speed, lanes, buﬀers, crossing

distance, and 13 other attributes

PBS Two collector urban

street

Stangl (2012) CEL Route directness score Community block-size Pedestrian Route

Directness Index

8diﬀerent block size

varying from

200 ft. X 200 ft. to

1000 ft. X 1000 ft.

Asadi-

Shekari, Moeinaddini,

and Zaly Shah (2012)

CEL and design

guidelines

NA Model 1: Slope, elevator, curb ramp, and

7 other attributes

Model 2: Traﬃc speed, pavement,

markings and 17 other attributes

PBS 1 street in Singapore NA

(Continued)

TRANSPORT REVIEWS 9

Table 2. Continued.

Research items

Attribute

selection

technique

Modelling speciﬁcations

Analysis method

No. of locations/

sample size/

observations

Goodness of

ﬁt/validation

measureDependent attribute Independent attributes

Asadi-Shekari et al.

(2014)

Citing from 20

design

guidelines

from

developed

nations

NA Traﬃc speed, lanes, buﬀers, mid block and 23

other attributes

PBS 1 street in the

campus –20

guidelines

reviewed

Not reported

Broad construct/s involved: users’perception

Sahani, Praveena, and

Bhuyan (2016)

CEL Overall satisfaction

score

Traﬃc, safety, comfort, maintenance and

aesthetics score

Multinomial Logit 1425 respondents Chi-square value =

505.5depicts good ﬁt.

70% of data used for

model ﬁt, remaining 30%

used to validate

Bivina, Parida, Advani,

and Parida (2018)

CEL NA Physical: Surface quality, width, obstruction,

vehicular conﬂict, continuity,

encroachment, crossing facility, security,

walk environment, comfort

PBS 2804 respondents

from 5 cities

Cronbach’s alpha > 0.7

assess internal

consistency

Bivina and Parida (2019) CEL Latent Exogenous:

Safety; Security;

Mobility &

infrastructure;

Comfort &

convenience

Latent Endogenous:

Perceived PLOS

scores from users

Traﬃc volume, traﬃc speed, police

patrolling, street lights, CCTV camera,

width of sidewalks, continuity,

encroachment, surface quality, pedestrian

amenities, bus shelter, cleanliness,

planning for disabled, obstruction

Structural Equation

Modelling

502 responses Normed Fit Index (NFI) =

0.92; Comparative Fit

Index (CFI) = 0.953;

Tucker Lewis Index (TLI)

= 0.939; Acceptable is

NFI, CFI, TLI > 0.9

Root Mean Square Error

(RMSEA) = 0.05;

Acceptable is RMSEA <

0.06

Broad constructs involved: users’perception + built environment

Christopoulou and

Pitsiava-Latinopoulou

(2012)

CEL NA Traﬃc factors, geometric/environmental

factors and pedestrian movement factors

PBS Application on one

location

Compared with 5 existing

methodology

qualitatively

Parvathi (2018) CEL Perceived user score Sidewalk condition, road characteristics,

interaction between pedestrians and other

modes, buﬀer, transit area and safety

PBS, inverse variance to

calculate weights

Over 100

respondents

Zannat, Raja, and Adnan

(2019)

CEL Model 1: Perceived

PLOS scores from

users

Model 2: Perceived

PLOS scores from

users

Model 3: Perceived

roadway conditions

Model 1: Perceived roadway conditions –

accessibility, safety, comfort and

attractiveness

Model 2: Physical feature measurement –

Footpath (width of sidewalk, lighting, etc.)

carriageway (median width, guard rail etc.)

and transit facilities (bus bay, sign etc.)

Model 3: Physical feature measurement

Model 1: Ordered probit

Model 2: Marginal

eﬀects

Model 3: MLR

Model 1: 413

responses

Model 2: 413

responses and

physical feature

survey from 88

points in the city

Model 3: 413

NR for any model

10 D. NAG ET AL.

responses and

physical feature

survey from 88

points in the city

Broad constructs involved: ﬂow characteristics + built environment

Karatas and Tuydes-

Yaman (2018)

CEL Pedestrian volume,

assessment score

Density, walkway width, buﬀer area, shade,

enclosure, motor vehicle, maintenance,

conﬂicts

Minimum PLOS of the

three methodology or

weighted average

method

81 road segments NA

Broad construct/s involved: (a) ﬂow characteristics (b) users’perception + built environment

Indian Highway Capacity

Manual (2018)

CEL Model 1: ﬂow rate

Model 2: Speed

Model 3: Space

Model 4: Users’score

Model 1, 2, 3: Density

Model 4: QoS (Bivina et al., 2018): Physical

and users’characteristics

Model 1, 2, 3: LR

Model 4: Bivina et al.,

(2018)–PBS, weighted

average method

Model 1, 2, 3: sample

size = 951

Model 4: NR

Broad construct/s involved: (a) users’perception (b) built environment + ﬂow characteristics

Marisamynathan and

Lakshmi (2016)

CEL Overall satisfaction

level

Sidewalk surface, presence of guardrails and

barriers, traﬃc volume, sidewalk width

Step-wise MLR 540 respondents R

= 0.935; 90% data used

for model ﬁt 10% for

validation. MAPE = 3.14%

and RMSE = 2.02%

Zhao et al. (2016) CEL Users’perception

scores

Flow rate, vehicular ﬂow, eﬀective width,

segregation facilities, frequency of barriers,

on-street parking, green looking ratio,

connected regions

Image processing and

Fuzzy neural network

87 sidewalks and

4300 responses

Accuracy = 0.94 compared

with the testing data set

Daniel et al. (2016) CEL Participants score Footpath width, road width, surface damage,

number of obstructions, pedestrian ﬂow

traﬃc volume

MLR 391 respondents

from 25 roads

= 0.97, Validation –

average error 1.28%

Sahani et al. (2017) CEL Model 1: Overall

Satisfaction

Model 2: Perception

scores

Model 1: Platoon size, traﬃc, safety, comfort,

maintenance and aesthetic score

Model 2: width, pedestrian volume,

obstruction, motorised and non-motorised

volume

Factor analysis and

discriminant analysis for

selecting variables; step-

wise MLR for PLOS

Model; GP for LOS

classiﬁcation

1825 respondents Model 1: NR

Model 2: R

= 0.972

Note: CEL: Citing from Existing Literature; LR: Linear Regression; MLR: Multiple Linear Regression; NA: Not Applicable; NR: Not Reported; PBS: Points-Based System

TRANSPORT REVIEWS 11

Table 3. PLOS service-level deﬁnitions and classiﬁcation techniques from diﬀerent studies (excerpt from Appendix 2).

Research items

Classiﬁcation

technique used

MOE used for PLOS

classiﬁcation

Service-level deﬁnitions

ABCDEF

Broad construct/s involved: ﬂow characteristics

Polus et al. (1983) None Density (ped/m

) <0.60 0.61–0.75 C

0.75–1.25

1.26–2.00

Not deﬁned Not deﬁned Not deﬁned

Area module (m

/ped) >1.67 1.66–1.33 C

1.33–0.80

0.80–0.50

Not deﬁned Not deﬁned Not deﬁned

Average speed (m/min) 0–40 40–50 C

50–75

75–95

Not deﬁned Not deﬁned Not deﬁned

Sahani and Bhuyan

(2013)

Aﬃnity Propagation

Clustering

Volume (ped/s/m) ≤0.052 >0.052–0.065 >0.065–0.081 >0.081–0.095 >0.095–0.114 >0.114

Space (m

/ped) >17.78–14.42 >11.3–14.42 >8.24–11.3 >7.82–8.24 >5.3–7.82 ≤5.3

speed (m/s) >1.53 >1.36–1.53 >1.14–1.36 >0.93–1.14 >0.71–0.93 ≤0.71

V/C ratio ≤0.4 >0.4–0.57 >0.57–0.76 >0.76–0.9 >0.9–1.0 >1

Sahani and Bhuyan

(2017)

AP, GA-Fuzzy & SOM in

ANN Clustering

methods

Volume (ped/s/m) ≤0.061 >0.61–0.081 >0.081–0.104 >0.104–0.127 >0.127–0.146 >0.146

Space (m

/ped) ≥16.53 <16.53 to 13.06 <13.06–9.91 <9.91–7.25 <7.25–4.48 ≤4.48

Speed (m/s) >1.21 >1.03–1.21 >0.88–1.03 >0.78–0.88 >0.62–0.78 ≤0.62

V/C ratio ≤0.34 >0.34–0.52 >0.52–0.67 .0.67–0.84 >0.84–1.0 >1.0

Broad construct/s involved: built environment

Stangl (2012) None Pedestrian route

directness score

85–100% 45–84% 30–44% 23–29% 7–22% 0–6%

Asadi-Shekari et al.

(2012)

None PLOS score generated

from the Disabled

PLOS and General

PLOS

80–100 60–79 40–59 20–39 1–19 0

Broad construct/s involved: users’perception

Sahani et al. (2016) None Overall satisfaction score <1.5 1.5 to <2.5 2.5 to <3.5 3.5 to <4.5 4.5 to 5.5 >5.5

Bivina et al. (2018) None Model scores >125 100–125 75–99 50–74 25–49 <25

Bivina and Parida

(2019)

None Perceived PLOS score Not deﬁned as per service levels

Broad constructs involved: users’perception + built environment

Christopoulou and

Pitsiava-

Latinopoulou

(2012)

None Assessment score 42–35 <35–28 <28–21 <21–14 <14–7<7–0

12 D. NAG ET AL.

Parvathi (2018) None Perception score 4.34502 to

5.64542

5.64543 to 6.49512 6.49513 to 7.79349 7.79350 to

9.09538

9.09539 to

10.39522

10.39523 to

11.8697

Zannat et al. (2019) None Perceived PLOS score Not deﬁned as per service levels

Broad constructs involved: ﬂow characteristics + built environment

Rastogi, Chandra,

and Mohan (2014)

None Space (m

/ped) >5.00 >2.22–5.00 >1.43–2.22 >1.00–1.43 >0.69–1.00 <0.69

Flow rate (ped/min/m) ≤18 >18–35 >35–51 >51–66 >66–73 >73

Karatas and Tuydes-

Yaman (2018)

None Volume (ped./15 min) Conceptual model proposed hence no service-level deﬁnition provided

Scores from visual

assessment

Broad construct/s involved: (a) ﬂow characteristics (b) users’perception + built environment

Mori and

Tsukaguchi (1987)

None Volume (ped/min/m) <20 20–78 78–108 >108 Not deﬁned Not deﬁned

Density (ped/m

) <0.2 0.2–0.8 0.8–1.5 >1.5 Not deﬁned Not deﬁned

Overall evaluation Not deﬁned as per service levels

Indian Road

Congress (2012)

None Volume (ped/min/m) ≤12 12–15 15–21 21–27 27–45 >45

Space (m

/ped.) >4.9 3.3–4.9 1.9–3.3 1.3–1.9 0.6–1.3 <0.6

Qualitative description –

users & built

Ideal walk

condition and

factors

aﬀecting PLOS

minimal

Reasonable condition

exists, factors

aﬀecting safety and

comfort exists

Basic condition but

signiﬁcant factors

aﬀecting safety and

comfort also exists

Poor condition,

safety and

comfort

minimal

Walking

condition

unsuitable

Severely

restricted

walking

environment

Indian Highway

Capacity Manual

(2018)

None (classiﬁed as per

landuse –only

commercial is shown

here)

Flow rate

(ped/min/m)

≤13 >13–19 >19–30 >30–47 >47–69 >69

QoS: Model score ≥124 <124–106 <106–70 <70–52 <52 Not deﬁned

Broad construct/s involved: (a) users’perception (b) built environment + ﬂow characteristics

Landis et al. (2001) None Respondents score ≤1.5 >1.5–2.5 >2.5–3.5 >3.5–4.5 >4.5–5.5 >5.5

Petritsch et al.

(2006)

None Respondents score ≤1.5 >1.5–2.5 >2.5–3.5 >3.5–4.5 >4.5–5.5 >5.5

Tan et al. (2007) None Participants’scores <2.0 2.0 to <2.5 2.5 to <3.0 3.0 to <3.5 3.5 to <4.0 4.0 and above

Dowling et al.

(2009)

None Participants’scores <1.5 1.5 to <2.5 2.5 to <3.5 3.5 to <4.5 4.5 to <5.5 5.5 and above

Daniel et al. (2016) None Respondents’

perception score

>8.5 >7.0–8.5 >6.0–7.0 >5.0–6.0 >4.0–5.0 ≤4.0

Sahani et al. (2017) Genetic Programming

(GP) clustering

Respondents’

perception score

≤1.8 >1.8 to 2.7 >2.7 to 3.5 >3.5 to 4.28 >4.28 to 5.3 >5.3

Zannat et al. (2019) None Perceived PLOS score Not deﬁned as per service levels

TRANSPORT REVIEWS 13

5.2. Attributes most repeated

Attributes involved in 47 studies were counted for repetitions and classiﬁed as per their

association with the broad constructs of ﬂow characteristics (FC), built environment (BE)

and users’perception (UP).The major challenge faced in calculating the frequency of

each attributes was in identifying the diﬀerent names assigned to essentially the same

attribute in diﬀerent studies. 389 diﬀerent attributes are used in the 47 studies, which

were classiﬁed and grouped as 44 distinct attributes.

Figure 5 suggests that attribute such as “Flow rate of pedestrians”, which has been

classiﬁed as FC type attribute, have the highest repetition across the 47 studies. It is to

be noted, however, that studies emanating from India use both ﬂow rate and pedestrian

space (area module) extensively. Among the BE attribute type, “width of sidewalk”is the

most widely used attribute, whereas among UP attribute type it is the “presence of lateral

separation”that is often repeated. However, speciﬁcally for studies originating in India,

“aesthetics”was the most used attribute under the UP broad construct category. The

results were compared to that of the Raad and Burke (2018) review, which validated

that “width of sidewalk”and “pedestrian ﬂow rate”were indeed the most used utilised

attributes.

It is worth mentioning that attributes are classiﬁed under FC, BE and UP based on their

approach of data collection. FC and BE constructs are quantitative whereas UP is qualitat-

ive in nature. FC and BE attributes are actual measurements of the features from the

ground and UP attributes are views, documented from users of the facility. To clarify

further, “presence of sidewalk”,“presence of lateral separation”, etc., although may be a

BE feature, but was classiﬁed as UP, since the studies using these attributes recorded

them as response of users’satisfaction.

5.3. Broad constructs involved in the studies

As is shown in Table 2 (and Appendix 1), each study was classiﬁed as FC, BE, UP or a

combination thereof, based on the use of attributes pertaining to the constructs and

their method of data collection. If they involved quantitative attributes like FC or BE

solely, they were classiﬁed as FC or BE respectively; alternately if the studies involved

qualitative variables like UP in conjunction with a quantitative attribute FC then such

studies are classiﬁed under “UP + FC”. There were studies which seemed to have uti-

lised attributes from all three constructs, however they were not used in a combined

fashion to estimate the PLOS measure. An example of such classiﬁcation seen in

Table 2 is “FC & BE + UP”. It can be seen from Figure 6, that the highest share of

studies were the ones that utilised attributes related to FC (13 out of 47) followed

by studies that utilised attributes pertaining to the “UP & FC + BE”(11 out of 47)

category.

It was also seen that 6 out of the 22 (i.e. 28%) studies attributed to developing

economies, were related to the “UP & FC + BE”category. The share of studies in this

category is the highest, all others being –FC (22%), BE (14%), UP (14%), “FC & BE +

UP”(9%), “FC + BE”(4%), and “BE + UP”(9%). Clearly, “UP & FC + BE”category is a

popular broad construct category amongst newly created PLOS models emanating

from developing countries.

14 D. NAG ET AL.

Figure 5. Most utilised (a) ﬂow characteristics; (b) built environment; (c) users’perception attribute

type.

TRANSPORT REVIEWS 15

5.4. Analysis techniques

Referring to Figure 7, we see that out of the 47 research items, 28 of them used regression

to estimate their PLOS model. The linear regression technique was utilised mainly for esti-

mating the ﬂow parameter relationships whereas multiple linear regression (MLR) was

used for quantifying pedestrian perception and analysing relationships. Clearly, regression

is the most preferred technique for estimation, especially MLR; however, the assumed

relationship may not be linear.

There are 10 studies which used an analytical points scale system (refer Figure 7). Asadi-

Shekari, Moeinaddini, and Zaly Shah (2014) and Christopoulou and Pitsiava-Latinopoulou

(2012) utilised guidelines from around the world to create weightages for the assessment

criteria in order to make their evaluation robust. Techniques listed under the “others”cat-

egory include –conjoint analysis, structural equation modelling, marginal eﬀects models,

artiﬁcial neural networks, clustering algorithm, and data visualisation techniques. One of

the studies used alternate modelling techniques (Zhao, Bian, Rong, Liu, & Shu, 2016),

where they utilised a fuzzy neural network, showed not only a more accurate model for

PLOS estimation, but also helped in the scientiﬁc categorisation of service level.

PLOS studies from developing countries were found to be inclined towards multiple

linear regression (28%) and analytical points scale system (22%).

5.5. Service-level categorisation

PLOS estimated using statistical techniques and analytical points system yields ﬁnal values

which are then categorised manually into LOS A, LOS B, LOS C, etc. But, manual interven-

tion in this process is deﬁning the service levels incorrectly as shown by Sahani and

Bhuyan (2015). As seen from Table 3 (and Appendix 2), only 5 out of the 47 (Sahani,

2013; Sahani, Ojha, & Bhuyan, 2017; Sahani & Bhuyan, 2015,2017; Zhao et al., 2016)

Figure 6. Break-up of broad constructs involved in the 45 studies reviewed.

16 D. NAG ET AL.

studies have used advanced modelling techniques like fuzzy analysis, neural network and

clustering algorithm to categorise the pedestrian service levels. The use of such advanced

soft computing and statistical tool will not only yield more accurate results but also

address the quantiﬁcation of cut-oﬀvalues (threshold values) as posed by Kadali and

Vedagiri (2016). The developing countries considered this problem to be signiﬁcant. All

the PLOS studies that have used a classiﬁcation technique were seen to be emanating

from the developing nations.

6. Critical discussions and conclusions

A systematic review of 47 PLOS studies and 8 review papers was conducted with an aim to

highlight the similarities/diﬀerences among the studies thereby updating the readers with

the state-of-the-art practices on sidewalk PLOS. This review considers the PLOS develop-

ment process as consisting of three distinct steps –(a) attribute selection; (b) model devel-

opment; and (c) service-level categorisation. Limitations of previous PLOS models and the

way forward in the development of newer PLOS models are also discussed in the following

subsections.

6.1. Attribute selection for PLOS development

The review found 389 attributes used across 47 studies. These attributes were not only

duplicate in nature, but were also utilising inconsistent terminology. Moreover, Table 2

(and Appendix 1) suggests that there is a lack of a common methodology that would

Figure 7. Break-up (in terms of number of studies) of analysis techniques involved.

TRANSPORT REVIEWS 17

otherwise help researchers/practitioners in selecting suitable attributes for their PLOS

studies. 46 out of 47 studies have picked their attributes from existing literature

without any rigour to determine if those attributes are reﬂective of the study area’s

walking environment. Only Hidayat, Choocharukul, and Kishi (2011) have sought

users’opinion on 27 factors and checked their suitability using factor analysis. This

helps in understanding the relevance of the attribute as perceived by users. For

example, the factor analysis by Hidayat et al. (2011) helps the readers to realise that

“vendor attraction”and “vendor problems”on sidewalk facilities are pertinent factors

for determining performance of such facilities, and this is especially relevant for devel-

oping economies.

Users’opinion may be further augmented by collecting experts’views in identifying

relevant factors for PLOS studies. This is because the PLOS measures are developed for

the usage and interpretation by practitioners and professionals, which in-turn would

help in designing interventions speciﬁc to the study area. Hence both users and

experts are important actors in PLOS development and it would be

intuitive to examine their opinion early on in the process i.e. during the attribute selec-

tion stage.

Studies have portrayed robust methodologies and used advanced techniques for cali-

brating PLOS models, however, similar rigour has not been seen while selecting attributes

for developing the PLOS. To avoid inputting irrelevant attributes at the beginning of the

process, there is a need for taking a step backward and focus on attribute selection

comprehensively.

6.2. Under-representation of the three broad constructs in conjunction

PLOS studies have exhibited a wide variety of approaches between 1971 and 2019; begin-

ning by closely mimicking the methodology of the traditional vehicular LOS, to a com-

bined quantitative and qualitative estimation of PLOS. In some cases, researchers were

visually assessing the environment, whereas others were recording assessments based

on the users. Early PLOS measures (1970s and 1980s) were related to the broad constructs

of FC, as they were solely using pedestrian/traﬃcﬂow parameters (Fruin, 1971; Polus,

Schofer, & Ushpiz, 1983; Pushkarev & Zupan, 1975; Tanaboriboon & Guyano, 1989).

Later on (1980s onward till late 1990s) qualitative PLOS assessment of the built environ-

ment, which relates to BE, was carried out by researchers (Dixon, 1996; Gallin, 2001;

Jaskiewicz, 2000; Sarkar, 1994). This was the phase when researchers understood that

such visual assessments were subjective, and hence began to record users’perception

(UP) (Khisty, 1994).

All these approaches were state-of-the-art before 2000s. However, Landis’model

(Landis et al., 2001) seemed to be the turning point of PLOS studies. Landis et al. (2001)

advocated a transferrable PLOS, which was based on the roadside characteristics, and

developed a model through MLR. This study was the ﬁrst which objectively quantiﬁed

pedestrian perception along a roadway segment using measurable traﬃc and roadway

variables. They utilised the mathematical expression shown in Equation (1) to carry out

stepwise regression. Subsequently researchers used built environment and traﬃc par-

ameters to characterise their PLOS model thereby taking a holistic approach by utilising

18 D. NAG ET AL.

more than just one broad construct.

PLOS Score =a1×f(lateral separation factors) +a2×f(traffic volume)

+a3×f(speed, vehicle type)

+a4×f(driveway access frequency and volume) +Constant

(1)

Following Landis et al.’s development, several other studies started developing and

experimenting with their approach of modelling, where users’perception was considered

as a dependent variable. Researchers applied this to diﬀerent Asian country contexts as

well, such as China (Meng, Zhu, & Zeng, 2014; Tan, Wang, Lu, & Bian, 2007; Zhao et al.,

2016), India (Marisamynathan & Lakshmi, 2016; Sahani et al., 2017), Thailand (Hidayat

et al., 2011) and Malaysia (Daniel et al., 2016). While this approach of modelling PLOS is

very intuitive and practical, it must be noted that practitioners applying this technique

do not collect users’perception to arrive at the potential PLOS score. Looking at Equation

(1), the developed model requires only visual assessment inputs of built physical charac-

teristics and traﬃcﬂow parameters to predict users’perception, which is then classiﬁed

into PLOS levels. Thus one could argue that such studies partially utilise the broad con-

structs, i.e. combining BE and FC to predict UP, rather than a combination of BE, FC and

UP to predict PLOS.Reviewing the broad constructs involved in all studies as shown in

Table 2 (and Appendix 1), it is seen that there is a large variation in the use of attributes

that relates to the three broad construct. Out of 47 studies, 29% were found to be associ-

ated with ﬂow characteristics (FC), 18% with built environment (BE), and 11% with users’

perception (UP). Remaining 42% studies were in combination with any two of the three

broad constructs. None of the studies were found to be associated with all three broad

constructs in conjunction. This suggests that a combined method needs to be developed

taking into account all the three broad constructs.

6.3. Modelling and classiﬁcation approaches for developing PLOS

There is a consistency across studies regarding techniques used for estimating the PLOS

model. It was found that statistical regression was the most favoured, with 60% of the

studies using this technique. Within the regression-based studies, simple linear regression

(SLR) and multiple linear regression (MLR) methods are the most popular ones. The good-

ness of ﬁt(R

) values for these models varied in the range of 0.21–0.972. Over-reliance of

these techniques in PLOS studies compels us to critique the linearity between dependent

and independent attributes used in such regressions, which may not always hold true. Fur-

thermore, the LOS concept has been regarded as a classiﬁcation problem by researchers

(Bhuyan & Nayak, 2017), but for classifying service levels, only 11% of studies utilised a

classiﬁcation technique based on MOEs. Remaining studies perform this categorisation

manually, using the judgment of the researcher, and thus the service-level deﬁnition

varies from study to study. For example, as seen from Table 3 (and Appendix 2),

Dowling et al. (2009), Landis et al. (2001) and Petritsch et al. (2006) had similar deﬁnition

of service levels i.e. letter-grade “B”is assigned when the score is in between 1.5 and 2.5,

“C”when the score is in between 2.5and 4.5 and so on; whereas Tan et al. (2007), who had

developed a PLOS measure similar to the Landis’method, used a diﬀerent service-level

deﬁnition –“B”when the score is in between 2.0 and 2.5, “C”when the score is in

between 2.5 and 3.0 and so on. Here the model score interval for each service-level

TRANSPORT REVIEWS 19

deﬁnition is equal (i.e. the diﬀerence between upper limit and lower limit of model scores

for each service level remains constant). When Sahani et al. (2017) apply Genetic Program-

ming clustering algorithm to the outputs on similar PLOS models, service-level deﬁnitions

changes as per the result of the clustering algorithm and the model score interval does not

remain equal. This indicates that equal service-level deﬁnition does not hold true, and as

such studies that utilise a categorisation technique provides a more eﬃcient service-level

categorisation rather than studies utilising researchers’judgement.

Machine learning models may be better techniques for developing PLOS measures.

Such models use the computational strength which has reached fruition in recent

years. Computers are made to “learn”and classify samples by “training”them accord-

ingly. There are two types of classiﬁcation –supervised and unsupervised. Supervised

classiﬁcation are done when the dependent variable can be observed and is used is

the modelling process. PLOS studies (Sahani & Bhuyan, 2017; Zhao et al., 2016) which

employ such classiﬁcation tend to utilise users’perceived overall score (broad con-

struct is UP) that was recorded during the data collection process. These studies

used UP much like Landis’method. Unsupervised classiﬁcation is employed when

the dependent variable is unobserved from the process. The output is generated

by understanding patterns within the dataset, this allows UP, BE and FC to be

included in the modelling process, as a part of the raw dataset being analysed.

Such an approach could be beneﬁcial because –(a) the service levels are generally

unobserved and should be interpretable from the three constructs; and (b) it bypasses

the need to classify service levels manually, which was the case, seen from previous

studies.

6.4. Role of network attributes in walking environment evaluation

An important feature of the built environment that is currently not being captured by

existing PLOS studies in the assessment of pedestrian networks. However, there exist

studies that measure network connectivity and accessibility (Bandara, Wirasinghe, Gur-

ofsky, & Chan, 1994; Dill, 2004; Hillier, Penn, Grajewski, & Xu, 1993; Raford & Ragland,

2004; Tal & Handy, 2012) based on the conﬁgurational structure of links and nodes in

the pedestrian network. Hillier et al. (1993) have argued the importance of network

conﬁguration and its relative eﬀects on both pedestrian movement and landuse attraction.

According to them, “attraction theory”(i.e. theories on movement of people, to and from

diﬀerent built forms or landuse with diﬀerent degree of attractions) does not talk about

the spatial conﬁguration of the urban links. There is ample evidence from existing litera-

ture that network plays an important role in route choice behaviour of pedestrians (Li &

Tsukaguchi, 2005; Muraleetharan & Hagiwara, 2007). As connectivity of pedestrian

network increases, travel distances decrease and route options increase, “allowing more

direct travel between destinations, and thereby, creating a more accessible and resilient

system”(Litman, 2004). Until now, the discussion on PLOS evaluation had been limited

to link level analyses, as was done for vehicular LOS assessment. An average pedestrian

trip-length ranges between 650 m and 1050 m (Arasan, Rengaraju, & Rao, 1994; Johar,

Jain, Garg, & Gundaliya, 2015; Rastogi & Krishna Rao, 2003) which is unlike vehicles that

can cover much longer distances. This aspect of a pedestrian trip is essential for a

network-wide assessment since there is a higher likelihood that links would be

20 D. NAG ET AL.

homogenous within short walking distances, rather than long driving links, and thereby

making the development of a network-wide PLOS much more meaningful.

Advances in Space Syntax techniques and analytic methods have been very impactful

in the past two decades. The ability of space-syntax based measure has been acknowl-

edged to be more impactful than environmental attributes of the built environment (i.e.

measurements and landuse characteristics) (Sharmin & Kamruzzaman, 2018). Therefore,

utilisation of such indices might be helpful for developing more eﬃcient PLOS models.

This view was supported by Raad and Burke (2018) where the authors acknowledge

that connectivity is an under-researched aspects in PLOS studies and Space Syntax mod-

elling techniques may help achieve more meaningful results.

7. Contribution of this review study to the body of knowledge

This paper builds upon the existing 6 review studies and 47 research papers that have

been published worldwide on the topic of PLOS. There are three distinct aspects of this

paper that adds to the body of knowledge on PLOS, and by doing so, distinguishes

itself from the existing review studies. Firstly, this study updates readers with the most

recent advancements, speciﬁcally in the ﬁeld of sidewalk PLOS measures, by reviewing

37 peer-reviewed journal articles, 6 indexed conference proceeding articles and 4 techni-

cal documents. The review range spanned from 1971 up to 2019, whereas the latest pub-

lished review article’s range was from 1971 to 2017. Findings from the six review articles

along with two other related review papers, on walkability indices, were also examined

and reported. Such a review of sidewalk PLOS studies in conjunction with walkability

indices has not been undertaken till date.

Secondly, this study reviews each PLOS study based on their distinct components. The

authors are of the view that each PLOS development follow three steps –(a) attribute

selection for PLOS; (b) modelling and calibration of the measure; and (c) service-level cat-

egorisation of the outputs. This component-based approach to understanding PLOS was

found to be absent in the other review papers even though the three components are

assessed in each of the 47 PLOS papers. By breaking it down in to three components,

the readers get an in-depth and clear understanding of the PLOS development process.

Table 2 (and Appendix 1) lists the PLOS studies as per their attribute selection procedure

and modelling approach, whereas, Table 3 (and Appendix 2) gives information about the

service-level deﬁnitions. Table 2 tells the readers how most studies do not follow any attri-

bute selection procedure, whereas Table 3 allows readers to compare service-level

deﬁnitions of diﬀerent studies, which was non-existent in the reviews till date. Further-

more, Table 3 exhibits that most studies categorised their service levels manually, which

may not be giving consistent and robust results.

Finally, this review evaluates each PLOS study from the point of view of the three broad

constructs, and strongly advocates the usage of a PLOS measure which is associated with

all the constructs in conjunction. Table 2 (Appendix 1) categorised each PLOS study as per

their association with the broad constructs and it was interesting to note that none of the

PLOS studies were associated with the three constructs in a combined manner. Further-

more, this study also identiﬁes a speciﬁc aspect of the built environment (one of the

three broad construct) that is not being discussed in most review papers. This aspect is

the pedestrian network and is shown to be an important component of the walking

TRANSPORT REVIEWS 21

experience that can hamper the performance of the built walking environment. Therefore,

the discussions included the possibility of deﬁning PLOS measures based on network attri-

butes and expand the PLOS deﬁnition over a network rather than just links.

Disclosure statement

No potential conﬂict of interest was reported by the authors.

Funding

This paper is a part of a research project titled “Smart and Integrated Pedestrian Network Design”

under the “Uchhatar Avishkar Yojana (UAY)”scheme. The Ministry of Human Resource & Develop-

ment (MHRD), Govt. of India; Ministry of Urban Development (MoUD), Govt. of India; Vikram Solar

Pvt. Ltd. and GMR Airport Developers Ltd. have jointly funded the project.

ORCID

Dipanjan Nag http://orcid.org/0000-0002-1192-2161

Arkopal Kishore Goswami http://orcid.org/0000-0003-1369-215X

Ankit Gupta http://orcid.org/0000-0003-1789-9502

Joy Sen http://orcid.org/0000-0002-4605-9273

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26 D. NAG ET AL.

Modelling speciﬁcations

Research items

Attribute selection

technique Dependent attribute Independent attributes Analysis method

No. of locations/sample

size/observations

Goodness of ﬁt/

validation measure

Broad construct/s involved: ﬂow characteristics

Fruin (1971) CEL Speed Area Module LR NR NR

Polus et al. (1983) CEL Model 1, 2, 3, 4:

Speed

Model 1, 2, 3, 4:

Density

LR 6 locations Model 1: R

= 0.602

Model 2: R

= 0.697

Model 3: R

= 0.918

Model 4: R

= 0.941

Davis and Braaksma

(1987)

CEL Time headway Speed Polynomial Regression 3 locations R

= 0.83

Tanaboriboon and

Guyano (1989)

CEL Speed Density LR NR NR

Highway Capacity

Manual (2000)

CEL Model 1: Speed;

Model 2: Flow rate;

Model 3: V/C ratio

Model 1, 2, 3, 4: Pedestrian space LR NR NR

Kim, Hallonquist,

Settachai, and

Yamashita (2006)

CEL NA Flow rate, pedestrian space,

sidewalk width, V/C ratio

Descriptive analysis and

data visualisation

16 screen lines NA

Bunevska Talevska

and Malenkovska

Todorova (2012)

CEL Pedestrian space Body ellipse, speed, acceleration,

position

Side friction micro-

simulation

3 residential streets NR

Sahani and Bhuyan

(2013)

CEL Flow rate, space, speed

and V/C ratio

Eﬀective width of sidewalk Follows HCM (2000);

Aﬃnity Propagation

(AP) clustering

algorithm

31 locations; 3764

pedestrians observed

Kim et al. (2014) CEL Evasive movements Eﬀective width, volume, landuse

characters

MLR 28 locations; 468 video

samples of 5 mins each

= 0.77 Validated with

perceived PLOS of 216

users

CEL Eﬀective width of sidewalk NR

(Continued)

Appendices

Appendix 1. Modelling information for PLOS studies reviewed

TRANSPORT REVIEWS 27

Continued.

Modelling speciﬁcations

Research items

Attribute selection

technique Dependent attribute Independent attributes Analysis method

No. of locations/sample

size/observations

Goodness of ﬁt/

validation measure

Sahani and Bhuyan

(2015)

Flow rate, space, speed

and V/C ratio

HCM (2000) methodology

and Self Organising

Maps (SOM) using

Analytical Neural

Network (ANN)

Silhouette, Davies-Bouldin,

Clinski-Harabasz and

Dunn Index

Raghuwanshi and

Tare (2016)

CEL Average pedestrian space V/C ratio of pedestrians, vehicles,

pedestrian crossing time, and

parking factors

MLR 9 street sections NR

Sahani and Bhuyan

(2017)

CEL Flow rate, space, speed

and V/C ratio

Eﬀective width of sidewalk HCM (2000) methodology

and three clustering

algorithms –AP, SOM in

ANN and Genetic

Algorithm (GA)

3764 pedestrians

observed

Clusters validated using a

number of index –

Silhouette, Davies-

Bouldin, Clinski-Harabasz

and Dunn

Cepolina et al. (2018) CEL Perceived comfort Interpersonal distances Local density method,

Voronoi diagram

395 pedestrians Validated in comparison

with HCM (2000)

Broad Construct/s involved: Built environment

Sarkar (1994) Researchers’insight NA NA Descriptive service levels Two cities of Europe NA

Dixon (1996) CEL NA sidewalk, conﬂicts, amenities,

vehicular LOS, maintenance, multi-

modality

PBS NR NA

Jaskiewicz (2000) CEL NA enclosure, path complexity,

articulation, transparency, buﬀer,

shade trees, and physical

components

PBS 12 locations for

assessment

Gallin (2001) CEL and stakeholder

consultation

NA Width, obstructions, volume,

security, connectivity,

environment, facilities, surface

quality, mix of users, conﬂict

PBS Not reported NA

Shekari and Zaly Shah

(2011)

Citing from 20

design guidelines

from developed

nations

NA Traﬃc speed, lanes, buﬀers, crossing

distance, and 13 other attributes

PBS Two collector urban

street

Stangl (2012) CEL Route directness score Community block-size Pedestrian Route

Directness Index

8diﬀerent block size

varying from 200 ft. X

200 ft. to 1000 ft. X

1000 ft.

28 D. NAG ET AL.

Asadi-Shekari et al.

(2012)

CEL and design

guidelines

NA Model 1: Slope, elevator, curb ramp,

and 7 other attributes

Model 2: Traﬃc speed, pavement,

markings and 17 other attributes

PBS 1 street in Singapore NR

Asadi-Shekari et al.

(2014)

Citing from 20

design guidelines

from developed

nations

NA Traﬃc speed, lanes, buﬀers, mid

block and 23 other attributes

PBS 1 street in the campus –

20 guidelines reviewed

Not reported

Broad construct/s involved: users’perception

Khisty (1994) CEL NA Safety, security, comfort,

attractiveness, convenience,

coherence, continuity

PBS, constant-sum,

paired-comparison

method

302 responses NA

Muraleetharan,

Adachi, Uchida,

Hagiwara, and

Kagaya (2004)

CEL Users’rating of proﬁles Width & Separation, obstructions,

ﬂow rate and bicycle events

Conjoint analysis 531 respondents Pearson’sR∼1 (near

perfect) and

Kendall’s Tau = 0.986

Muraleetharan and

Hagiwara (2007)

CEL Model 1: Respondents

rating

Model 2: Alternative

routes

Model 1: Width & Separation,

obstructions, ﬂow rate and bicycle

events

Model 2: walking distance and LOS

score

Conjoint analysis &

Multinomial logit (MNL)

model

346 respondents and 215

sidewalks

Model 1: Not reported

Model 2: Pseodo-R

0.183, % of correct

prediction = 74%

Sahani et al. (2016) CEL Overall satisfaction score Traﬃc, safety, comfort, maintenance

and aesthetics score

MNL 1425 respondents Chi-square value =

505.5depicts good ﬁt.

70% of data used for

model ﬁt, remaining 30%

used to validate

Bivina et al. (2018) CEL NA Physical: Surface quality, width,

obstruction, vehicular conﬂict,

continuity, encroachment,

crossing facility, security, walk

environment, comfort

PBS 2804 respondents from 5

cities

Cronbach’s alpha > 0.7

assess internal

consistency

Bivina and Parida

(2019)

CEL Latent Exogenous: Safety;

Security; Mobility &

infrastructure; Comfort

& convenience

Latent Endogenous:

Perceived PLOS scores

from users

Traﬃc volume, traﬃc speed, police

patrolling, street lights, CCTV

camera, width of sidewalks,

continuity, encroachment, surface

quality, pedestrian amenities, bus

shelter, cleanliness, planning for

disabled, obstruction

Structural Equation

Modelling

502 responses Normed Fit Index (NFI) =

0.92; Comparative Fit

Index (CFI) = 0.953;

Tucker Lewis Index (TLI)

= 0.939; Acceptable is

NFI, CFI, TLI > 0.9

Root Mean Square Error

(RMSEA) = 0.05;

(Continued)

TRANSPORT REVIEWS 29

Continued.

Modelling speciﬁcations

Research items

Attribute selection

technique Dependent attribute Independent attributes Analysis method

No. of locations/sample

size/observations

Goodness of ﬁt/

validation measure

Acceptable is RMSEA <

0.06

Broad constructs involved: users’perception + built environment

Christopoulou and

Pitsiava-

Latinopoulou (2012)

CEL NA Traﬃc factors, geometric/

environmental factors and

pedestrian movement factors

PBS Application on one

location

Compared with 5 existing

methodology

qualitatively

Parvathi (2018) CEL Perceived user score Sidewalk condition, road

characteristics, interaction

between pedestrians and other

modes, buﬀer, transit area and

safety

PBS, inverse variance to

calculate weights

Over 100 respondents NA

Zannat et al. (2019) CEL Model 1: Perceived PLOS

scores from users

Model 2: Perceived

PLOS scores from users

Model 3: Perceived

roadway conditions

Model 1: Perceived roadway

conditions –accessibility, safety,

comfort and attractiveness

Model 2: Physical feature

measurement –Footpath (width

of sidewalk, lighting, etc.)

carriageway (median width, guard

rail etc.) and transit facilities (bus

bay, sign, etc.)

Model 3: Physical feature

measurement

Model 1: Ordered probit

Model 2: Marginal

eﬀects

Model 3: Multiple linear

regression

Model 1: 413 responses

Model 2: 413 responses

and physical feature

survey from 88 points

in the city

Model 2: 413 responses

and physical feature

survey from 88 points

in the city

NR for any model

Broad constructs involved: ﬂow characteristics + built environment

Rastogi et al. (2014) CEL Model 1 & 2: LOS values

obtained from a

diﬀerent study

Model 1 & 2: Pedestrian ﬂow,

Sidewalk width, obstruction

Model 1 & 2: Stepwise

MLR and Pearson’s

correlation analyses

Sample size: 517 Model 1: R

= 0.899

Model 2: R

= 0.899

Karatas and Tuydes-

Yaman (2018)

CEL Pedestrian volume,

assessment score

Density, walkway width, buﬀer area,

shade, enclosure, motor vehicle,

maintenance, conﬂicts

Minimum PLOS of the

three methodology or

weighted average

method

81 road segments NA

Broad construct/s involved: (a) ﬂow characteristics (b) users’perception + built environment

Mori and Tsukaguchi

(1987)

CEL Model 1: speed

Model 2: Participants

scores

Model 1: density

Model 2: eﬀective sidewalk width,

green ratio, sidewalk type

Model 1: LR

Model 2: MLR

Model 1: NR

Model 2: 35

respondents

Model 1: NR

Model 2: R

= 0.85

CEL NR NR

30 D. NAG ET AL.

Highway Capacity

Manual (2010)

Model 1: Participants

scores

Model 2: Pedestrian

spacing

Model 1: Eﬀective width of sidewalk,

width of bicycle lane, buﬀer,

vehicular traﬃc speed and

volume, presence of curb;

Model 2: Eﬀective width of

sidewalk, width of bicycle lane,

lateral

Separation, walking speed

Model 1:

Step-wise MLR

Model 2: LR

Indian Road Congress

(2012)

CEL NA Pedestrian space, ﬂow rate, speed.

Qualitative descriptions of built

environment

Quantitative –PLOS

values adopted from

HCM (2000)

Qualitative –description

of LOS values

NR NR

Indian Highway

Capacity Manual

(2018)

CEL Model 1: ﬂow rate

Model 2: Speed

Model 3: Space

Model 4: Users’score

Model 1, 2, 3: Density

Model 4: QoS (Bivina et al., 2018):

Physical and users’characteristics

Model 1, 2, 3: LR

Model 4: Bivina et al.,

(2018)–PBS, weighted

average method

Model 1, 2, 3: sample size

= 951

Model 4: NR

Broad construct/s involved: (a) users’perception (b) built environment + ﬂow characteristics

Landis et al. (2001) CEL Respondents score Lateral separation factors, motor

vehicle volume, motor vehicle

speed, motor vehicle mix,

driveway access frequency and

volume

Stepwise MLR 75 respondents; 42

segments

= 0.85

Petritsch et al. (2006) CEL Respondents score Crossing width (per mile) at conﬂict

locations, Average 15-min volume

of vehicular traﬃc adjacent to the

sidewalk

Pearson’s correlation

analysis, hypothesis

tests, and MLR

506 participants R

= 0.70

Jensen (2007) NR Share of Participants

stating a particular

score

Vehicular traﬃc volume, speed, type

of facility, width of pedestrian

facility, volume of pedestrians,

presence of trees, parked cars and

medians

Cumulative Logit Model

stepwise regression

407 participants R

= 0.55

Max. rescaled R

=0.57

Tan et al. (2007) CEL Response of users Pedestrian and bicycle volume,

driveway access frequency,

distance between sidewalk and

vehicle lane

Step-wise MLR 395 observations and 12

roadway segment

Dowling et al. (2009) NR Response of users Eﬀective width of sidewalk, buﬀer,

speed of vehicles, volume of

vehicles, curb

MLR 140 respondents were

showed 90 video clips

(Continued)

TRANSPORT REVIEWS 31

Continued.

Modelling speciﬁcations

Research items

Attribute selection

technique Dependent attribute Independent attributes Analysis method

No. of locations/sample

size/observations

Goodness of ﬁt/

validation measure

Hidayat et al. (2011) Factor analysis of 27

factors from

existing literature

based on users’

opinion

Model 1, 2, 3:

Perception of

pedestrian

Model 1: comfort, vendor attraction

Model 2: comfort, vendor

problems

Model 3: comfort, vendor

problems, pedestrian volume,

interaction vendors

MLR 1072 respondents from

Bangkok; 523 from

Jakarta

Model 1: R

= 0.27

Model 2: R

= 0.21

Model 3: R

= 0.24

Meng et al. (2014) CEL Model 1: Respondents

score (main)

Model 2: Cross-section

var. (comp. of 1)

Model 3:

Comprehensive var. of

street (comp. of 1)

Model 4: Log value of

Auxiliary street var.

(comp. of 1)

Model 1: Cross-section, ped. ﬂow,

obstacles, comprehensive,

auxiliary

Model 2: width, elevation diﬀ., and

separators exists

Model 3: quality of pavement

Model 4: utility variables like light,

shade, garbage bins, recreational

and public health

MLR 227 respondents from 2

locations

Model 1: R

= 0.4

Model 2: R

= 0.4

Model 3: R

= 0.4

Model 4: NR

Marisamynathan and

Lakshmi (2016)

CEL Overall satisfaction level Sidewalk surface, presence of

guardrails and barriers, traﬃc

volume, sidewalk width

Step-wise MLR 540 respondents R

= 0.935; 90% data used

for model ﬁt 10% for

validation. MAPE = 3.14%

and RMSE = 2.02%

Zhao et al. (2016) CEL Users’perception scores Flow rate, vehicular ﬂow, eﬀective

width, segregation facilities,

frequency of barriers, on-street

parking, green looking ratio,

connected regions

Image processing and

Fuzzy neural network

87 sidewalks and 4300

responses

Accuracy = 0.94 compared

with the testing data set

Daniel et al. (2016) CEL Participants score Footpath width, road width, surface

damage, number of obstructions,

pedestrian ﬂow traﬃc volume

MLR 391 respondents from 25

roads

= 0.97, Validation –

average error 1.28%

Sahani et al. (2017) CEL Model 1: Overall

Satisfaction

Model 2: Perception

scores

Model 1: Platoon size, traﬃc, safety,

comfort, maintenance and

aesthetic score

Model 2: width, pedestrian

volume, obstruction, motorised

and non-motorised volume

Factor analysis and

discriminant analysis for

selecting variables; step-

wise MLR for PLOS

Model; GP for LOS

classiﬁcation

1825 respondents Model 1: NR

Model 2: R

= 0.972

Note: CEL: Citing from Existing Literature; LR: Linear Regression; MLR: Multiple Linear Regression; NA: Not Applicable; NR: Not Reported; PBS: Points-Based System

32 D. NAG ET AL.

Appendix 2. PLOS service-level deﬁnitions and classiﬁcation techniques from diﬀerent studies

Research items

Classiﬁcation

technique used

MOE used for PLOS

classiﬁcation

Service-level deﬁnitions

AB CD E F

Broad Construct/s involved: ﬂow characteristics

Fruin (1971) None Area module (ft

/ped) >35 25–35 15–25 10–15 5–10 <5

Volume (ped/min/ft) 7 7–10 10–15 15–20 20–25 >25

Polus et al. (1983) None Density (ped/m

) <0.60 0.61–0.75 C

0.75–

1.25

1.26–2.00

Not deﬁned Not deﬁned Not deﬁned

Area module (m

/ped) >1.67 1.66–1.33 C

1.33–

0.80

0.80–0.50

Not deﬁned Not deﬁned Not deﬁned

Average speed (m/

min)

0–40 40–50 C

50–75

75–95

Not deﬁned Not deﬁned Not deﬁned

Davis and Braaksma

(1987)

None Volume (ped/min/m) A+

<37

37–46

46–57 57–68 68–75 75–57 <57

Area module (m

/ped) A+

>2.3

1.7–2.3

1.3–1.7 1.0–1.3 0.8–1.0 0.7–0.8 <0.7

Speed (m/s) A+

>1.4

1.3–1.4

1.2–1.3 1.1–1.2 1.0–1.1 0.7–1.0 <0.7

Tanaboriboon and

Guyano (1989)

None Area module (m

/ped) >2.38 1.60–2.38 0.98–1.60 0.65–0.98 0.37–0.65 <0.37

Volume (ped/min/m) <28 28–40 40–61 61–81 81–101 >101

Highway Capacity

Manual (2000)

None Space (m

/ped) >5.6 >3.7–5.6 >2.2–3.7 >1.4–2.2 >0.75–1.4 ≤0.75

ﬂow rate (ped./m/m

)≤16 >16–23 >23–33 >33–49 >49–75 >75

speed (m/s) >1.30 >1.27–1.30 >1.22–1.27 >1.14–1.22 >0.75–1.14 ≤0.75

V/C ratio ≤0.21 >0.21–0.31 >0.31–0.44 >0.44–0.65 >0.65–1.0 >1.0

Kim et al. (2006) None Space (ft

/ped) >60 >40–60 >24–40 >15–24 >8–15 ≤8

Flow rate (ped/min/ft) ≤5>5–7>7–10 >10–15 >15–23 >23

Bunevska Talevska and

Malenkovska

Todorova (2012)

None Space (ft

/ped) >60 >40–60 >24–40 >15–24 >8–15 ≤8.0

Sahani and Bhuyan

(2013)

Aﬃnity propagation

clustering

Volume (ped/s/m) ≤0.052 >0.052–0.065 >0.065–0.081 >0.081–0.095 >0.095–0.114 >0.114

Space (m

/ped) >17.78–14.42 >11.3–14.42 >8.24–11.3 >7.82–8.24 >5.3–7.82 ≤5.3

speed (m/s) >1.53 >1.36–1.53 >1.14–1.36 >0.93–1.14 >0.71–0.93 ≤0.71

(Continued)

TRANSPORT REVIEWS 33

Continued.

Research items

Classiﬁcation

technique used

MOE used for PLOS

classiﬁcation

Service-level deﬁnitions

AB CD E F

V/C ratio ≤0.4 >0.4–0.57 >0.57–0.76 >0.76–0.9 >0.9–1.0 >1

Kim et al. (2014) None Evasive movements

(ped/min/m)

≤3.58 ≤6.32 ≤10.13 ≤13.06 ≤19.00 Over 19.00

space (m

/ped) ≥3.30 ≥2.00 ≥1.40 ≥0.90 ≥0.38 <0.38

Flow rate (ped/min/m) ≤20 ≤32 ≤46 ≤70 ≤106 >106

speed (m/s) ≥1.25 ≥1.20 ≥1.15 ≥1.03 ≥0.67 <0.67

Sahani and Bhuyan

(2015)

Self-organising maps in

analytical neural

networks

Space (m

/ped) >15.67 >11.94–15.67 >9.07–11.94 >6.49–9.07 >4.48–6.94 ≤4.48

Flow rate (ped/s/m) ≤0.063 >0.063–0.081 >0.081–0.103 >0.103–0.133 >0.133–0.145 >0.145

Raghuwanshi and Tare

(2016)

None Space (m

/ped) >4.9 3.3–4.9 1.9–3.3 1.3–1.9 0.6–1.3 <0.6

Sahani and Bhuyan

(2017)

AP, GA-Fuzzy & SOM in

ANN Clustering

methods

Volume (ped/s/m) ≤0.061 >0.61–0.081 >0.081–0.104 >0.104–0.127 >0.127–0.146 >0.146

Space (m

/ped) ≥16.53 <16.53 to 13.06 <13.06–9.91 <9.91–7.25 <7.25–4.48 ≤4.48

Speed (m/s) >1.21 >1.03–1.21 >0.88–1.03 >0.78–0.88 >0.62–0.78 ≤0.62

V/C ratio ≤0.34 >0.34–0.52 >0.52–0.67 .0.67–0.84 >0.84–1.0 >1.0

Cepolina et al. (2018) None Density (ped./m

) No clear

deﬁnition,

density has

been

compared

with HCM

(2000) LOS

Broad construct/s involved: built environment

Sarkar (1994) None Qualitative

descriptions of LOS

Highest here Safety

Security

Comfort

Continuity

System

coherence

Attractiveness

Lowest here

Dixon (1996) None Scores assigned by

visual assessment of

facilities

17–21 14–17 14–11 11–73–7<3

Jaskiewicz (2000) None Final scores from visual

assessment

4.0–5.0 3.4–3.9 2.8–3.3 2.2–2.7 1.6–2.1 1.0–1.5

Gallin (2001) None Final scores from visual

assessment

>132 101–131 69–100 37–68 <36 Not deﬁned

34 D. NAG ET AL.

Shekari and Zaly Shah

(2011)

None Weighted average

PLOS% score

80–100 60–79 40–59 20–39 1–19 0

Stangl (2012) None Pedestrian route

directness score

85–100% 45–84% 30–44% 23–29% 7–22% 0–6%

Asadi-Shekari et al.

(2012)

None PLOS score generated

from the Disabled

PLOS and General

PLOS

80–100 60–79 40–59 20–39 1–19 0

Asadi-Shekari et al.

(2014)

None Weighted average

PLOS% score

80–100 60–79 40–59 20–39 1–19 0

Broad construct/s involved: users’perception

Khisty (1994) None Users’perception of

satisfaction

5 points 4 points 3 points 2 points 1 points 0 points

Muraleetharan et al.

(2004)

None Utility scores Not deﬁned as

per service

levels –utility

value

decreases

from A to F

(linear

relationship)

Muraleetharan and

Hagiwara (2007)

None Utility scores High Medium Low

Sahani et al. (2016)None Overall satisfaction

score

<1.5 1.5 to <2.5 2.5 to <3.5 3.5 to <4.5 4.5–5.5 >5.5

Bivina et al. (2018) None Model scores >125 100–125 75–99 50–74 25–49 <25

Bivina and Parida

(2019)

None Perceived PLOS score Not deﬁned as

per service

levels

Broad constructs involved: users’perception + built environment

Christopoulou and

Pitsiava-Latinopoulou

(2012)

None Assessment score 42–35 <35–28 <28–21 <21–14 <14–7<7–0

Parvathi (2018) None Perception score 4.34502–

5.64542

5.64543–6.49512 6.49513–7.79349 7.79350–9.09538 9.09539–10.39522 10.39523–

11.8697

Zannat et al. (2019) None Perceived PLOS score Not deﬁned as

per service

levels

(Continued)

TRANSPORT REVIEWS 35

Continued.

Research items

Classiﬁcation

technique used

MOE used for PLOS

classiﬁcation

Service-level deﬁnitions

AB CD E F

Broad constructs involved: ﬂow characteristics + built environment

Rastogi et al. (2014) None Space (m

/ped) >5.00 >2.22–5.00 >1.43–2.22 >1.00–1.43 >0.69–1.00 <0.69

Flow rate (ped/min/m) ≤18 >18–35 >35–51 >51–66 >66–73 >73

Karatas and Tuydes-

Yaman (2018)

None Volume (ped./15 min) Conceptual

model

proposed

hence no

service-level

deﬁnition

provided

Scores from visual

assessment

Broad construct/s involved: (a) ﬂow characteristics (b) users’perception + built environment

Mori and Tsukaguchi

(1987)

None Volume (ped/min/m) <20 20–78 78–108 >108 Not deﬁned Not deﬁned

Density (ped/m

) <0.2 0.2–0.8 0.8–1.5 >1.5 Not deﬁned Not deﬁned

Overall evaluation Not deﬁned as

per service

levels

Highway Capacity

Manual (2010)

None, worse of both

PLOS grades is used as

ﬁnal grade

Space (ft

/ped) >60 >40–60 >24–40 >15–24 >8–15 ≤8.0

participants’(model)

score

≤2.0 >2–2.75 >2.75–3.50 >3.50–4.25 >4.25–5.00 >5.00

Indian Road Congress

(2012)

None Volume (ped/min/m) ≤12 12–15 15–21 21–27 27–45 >45

Space (m

/ped.) >4.9 3.3–4.9 1.9–3.3 1.3–1.9 0.6–1.3 <0.6

Qualitative description

–users & built

Ideal walking

condition and

factors

aﬀecting PLOS

minimal

Reasonable condition

exists, factors

aﬀecting safety and

comfort exists

Basic condition

but signiﬁcant

factors aﬀecting

safety and

comfort also

exists

Poor condition,

safety and

comfort minimal

Walk condition

unsuitable

Severely

restricted

walking

environment

Indian Highway

Capacity Manual

(2018)

None (classiﬁed as per

landuse –only

commercial is shown

here)

Flow rate

(ped/min/m)

≤13 >13–19 >19–30 >30–47 >47–69 >69

QoS: Model score ≥124 <124–106 <106–70 <70–52 <52 Not deﬁned

Broad construct/s involved: (a) users’perception (b) built environment + ﬂow characteristics

Landis et al. (2001) None Respondents score ≤1.5 >1.5–2.5 >2.5–3.5 >3.5–4.5 >4.5–5.5 >5.5

36 D. NAG ET AL.

Petritsch et al. (2006) None Respondents score ≤1.5 >1.5–2.5 >2.5–3.5 >3.5–4.5 >4.5–5.5 >5.5

Jensen (2007) None Share of participants

with level of

satisfaction

>50% very

satisﬁed

>50% moderately

satisﬁed and <50%

very satisﬁed

>50% little

satisﬁed and <

50% moderately

satisﬁed

>50% little

dissatisﬁed and

<50% little

satisﬁed

>50% moderately

dissatisﬁed and

<50% little

dissatisﬁed

>50% very

dissatisﬁed

Tan et al. (2007) None Participants’scores <2.0 2.0 to <2.5 2.5 to <3.0 3.0 to <3.5 3.5 to <4.0 4.0 and above

Dowling et al. (2009) None Participants’scores <1.5 1.5 to <2.5 2.5 to <3.5 3.5 to <4.5 4.5 to <5.5 5.5 and above

Hidayat et al. (2011) None Participants’scores >9.0 >7.0–9.0 >5.0–7.0 >3.0–5.0 >2.0–3.0 2.0 or below

Meng et al. (2014) None Respondents’score ≤1.5 >1.5–2.5 >2.5–3.5 >3.5–4.5 >4.5 Not deﬁned

Marisamynathan and

Lakshmi (2016)

None Level of satisfaction <15% 15–30% 30–45% 45–60% 60–85% >85%

Zhao et al. (2016) Fuzzy Neural Network Pedestrian satisfaction

scores

10–98 7 6 5 4–1

Daniel et al. (2016) None Respondents’

perception score

>8.5 >7.0–8.5 >6.0–7.0 >5.0–6.0 >4.0–5.0 ≤4.0

Sahani et al. (2017) Genetic Programming

(GP) clustering

Respondents’

perception score

≤1.8 >1.8–2.7 >2.7–3.5 >3.5–4.28 >4.28–5.3 >5.3

TRANSPORT REVIEWS 37

Pedestrian-oriented development in Beirut: A framework for estimating urban design impacts on pedestrian flows through modeling, participatory design, and scenario analysis

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Jun 2024
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Sidewalk networks: Review and outlook

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COMPUT ENVIRON URBAN

Addressing pedestrian perceived externalities influenced by motor vehicles: A perspective from curb space typologies

Article

Dec 2023
TRANSPORT RES A-POL

Pedestrian externalities are usually generated by motor vehicles on urban infrastructure. There is a part of such infrastructure, called curb space, that separates pedestrians from motor vehicles. The literature proposes four main curb space typologies regarding the right-of-way (i.e., no lateral separation, lateral separation with no vertical barriers, lateral separation with vertical barriers, and on-street parking). However, there is little research reporting on how pedestrians perceive the externalities, or on the effects of externalities considering the previously mentioned curb space typologies. The purpose of this study is to identify the influences of externalities on pedestrians from the latter’s perspective and considers their interaction with the built environment. To do so, we collected 1014 pedestrian responses related to their relationship with motor vehicles on 30 different sidewalks and some objective information (e.g., sidewalk width) on those sidewalks. Using a structural equation model approach, we identified a latent variable related with the pedestrian perceived externalities, which was defined based on a multiple indicators and multiple causes model for each of the curb space typologies. It was found that socio-demographic characteristics have a greater influence on the perceived externalities on curb spaces with no vertical barriers. In contrast, for curb spaces with vertical barriers, it is the built environment and operational characteristics that have a greater influence. We also identified the built environment and operational attributes influencing the perceived externalities on each of the curb space typologies. This research provides the tools to propose public policies related to transportation infrastructure interventions to reduce pedestrian perceived externalities.

Improving Walkability in Beirut: An Approach Using Pedestrian Modeling, Participatory Design, and Scenario Analysis

Preprint

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Jan 2023

Investigation of pedestrian and vehicle level of service regulation for Hacettepe Sıhhiye campus

Article

Feb 2024

Roads and sidewalks of Hacettepe Campus Children's Emergency were investigated in order to determine the congestion in the "emergency zone" in this area and improvement effects to different road quality methods were discussed. Both level of service of roads (LOS) and sidewalks (PLOS) were studied by using different methods as Highway Capacity Manual (HCM), Landis and Australian methods. As the result of study, since the terrain in the region is not suitable for vehicles, the pedestrian path was narrowed to reduce the traffic on the vehicle road and significantly reduce the problem. In addition, the methods used in the PLOS calculation were found to be deficient in terms of applicability. When comparing the different methods AUSTRALIAN method more realistic results as it has more generalizable perspective than others in this study.

Investigating the pedestrian capability, kinetic in strengthening the identity and social cohesion of cities Case study: Comparative analysis of the central context of Naqadeh and Qorveh cities

Article

May 2022

Introduction Urban spaces are one of the most obvious areas of manifestation of identity, culture and civilization of urban society. Due to its prominent role in the economic, physical, social and political structure of the city, the central context of cities has always been in the focus of attention of experts. Following the physical expansion of cities and the prominent role of the car factor, urban communities have gradually witnessed the decline of environmental and spatial qualities in terms of social solidarity and cohesion. In the meantime, the implementation of sidewalks following the strengthening of social life, indigenous identity and human-centered urban realization has always become an effective policy and strategy at the level of urban communities. In this regard, the main purpose of the present study is a comparative study of the feasibility of creating sidewalks in the central part of the cities of Naqadeh and Qorveh with the aim of strengthening identity, cohesion and social solidarity in the city and seeks to answer the following questions. Is: What is the level of correlation between the components of road construction and identity strengthening and social cohesion and solidarity? And the central context of which of the monocultural cities of Naqadeh and Qorveh can be implemented with the aim of strengthening social cohesion and identity? Methodology In the present study, with a practical purpose, a descriptive-analytical method and using document selection and library methods, the main concepts such as pedestrianism, identity and social cohesion are explained and the main components for specialized evaluation. The research has been extracted. the statistical population and sample size of the present study includes experts, thinkers and specialists in the field of urban sciences and all indigenous citizens of each of the study cities. The sample for the cities of Naqadeh and Qorveh is equal to 383 cases. Also, 30 samples as a targeted sample size from the statistical community of urban experts and experts have been used to prioritize research indicators and sub-indicators. Then, using a questionnaire and observation and interview methods with experts and people, the degree of correlation between the main components of the research and the level of desirability and compatibility of selected indicators and sub-indicators of the research and determining the superior option has been determined. In addition, to ensure the validity and reliability of the questionnaire, the views of the statistical community were used and the Cronbach's alpha test was calculated to be 0.982. Quantitative data analysis method is derived from Kolmogorov-Smirnov tests, Pearson correlation and Shannon and Cocoso entropy techniques. The top and final option is selected. In the last stage, in order to facilitate the implementation of the road in the superior option and to achieve favorable conditions in terms of social identity, solidarity and social cohesion among different segments of the people, effective and purposeful suggestions have been presented. Results and Discussions The results of Kolmogorov-Smirnov quantitative methods and Pearson correlation show that there is a direct and significant relationship between the components of implementation and strengthening of identity and social cohesion. Also, a correlation coefficient of 0.965 between the two components of road construction and strengthening urban cohesion and identity indicates a positive and strong correlation. According to the results of Shannon entropy method, sub-indices of improvement of collective spaces and topographic conditions have the highest and lowest level of importance and priority among other sub-indices in the implementation of road construction, respectively. The results of Cocoso method indicate that the central texture of Naqadeh city has more favorable conditions in terms of social and economic indicators and has an unfavorable situation in the characteristic feature of appearance and urban landscape. Meanwhile, in the central part of Qorveh city, the situation of social indicators and the characteristics of urban appearance and landscape are at an inappropriate level. It has also been in a good position compared to others in terms of natural characteristics, use and performance. According to the results and in general terms, the central texture of Naqadeh city with a final coefficient of 4.252 has more favorable conditions than the central texture of Qorveh city with a weight of 1.83 in terms of road construction feasibility. Conclusion According to the results of quantitative methods (based on statistical tests) and analysis of research findings, in order to achieve a suitable situation in the city of Naqadeh, purposeful and efficient suggestions have been presented. - Utilization of indigenous elements (elements, fountains, ...) in order to strengthen the social and cultural identity of the city - Creating suitable health spaces according to its ability - Supporting the presence of traditional retailers (vendors) and allocating spaces for their establishment - Appropriate role modeling of officials, managers and urban professionals from the valuable experiences of successful communities - Special attention and emphasis on the allocation of appropriate urban furniture - Reconstruction and renovation of some commercial functions in the area for the construction of commercial complexes - Special attention and emphasis on the urban beautification approach - Efforts to increase the level of mixing of uses - Utilization of stable and compatible environmental conditions - Emphasis on increasing sustainable social interactions between people and related organs and organizations to achieve the desired situation - Utilizing more stable modes of transportation in the study area (such as bicycles) and designing a special route for it - Assigning a separate route for the traffic of special affairs vehicles - Organizing and developing the use of green space and recreation-leisure - Creating and developing arrangements in order to revitalize the study environment around the clock (24-hour city) - Considering the principles of effective planning and design for the disabled and the elderly - And organizing the existing urban infrastructure while paying attention to future developments Keywords: Sidewalk, Identity and Social Cohesion, Central Context, Naqadeh, Qorveh

A Review on Pedestrian Level of Service for Sidewalks

Conference Paper

Jan 2024

Walking is a basic and environmentally friendly mode of transportation. For encourage walking, the walking facilities need to be designed and maintained properly. The performance of pedestrian facilities needs to be measured to enhance the popularity of walking as a mode which is termed as Pedestrian Level of Service (PLOS). Several studies have been conducted so far regarding the PLOS for sidewalks. The present study attempts to give a comprehensive overview of the studies conducted on PLOS for sidewalks using Preferred Reporting Items for Systematic Reviews and Metra-Analyses (PRISMA) guidelines. The overview was carried out focusing on the literature published till 2022 all over the world. A total of 25 papers obtained from Google Scholar were reviewed. The main objective of the study was to analyze the available literature on the basis of study locations, methods of data collection, parameters considered and analysis techniques used. Overall findings across the literature reveals that a large number of studies were conducted in India. It was found that the dimensions of the sidewalk were the factor that was most frequently considered in most of the studies. Regression analysis was the most commonly used model to analyze the PLOS. The key insights and limitations of the study are discussed. In the end, conclusions and scope of further research are also presented.

Making walking irresistible: enabling level-of-service measures to achieve their potential

Article

Jan 2023

How to develop the walking environment for its ‘consumers’? A conjoint answer derived from people's perception of link and network

Article

Full-text available

Oct 2023

Future-oriented urban planning will continue to uphold the principles of accessible and walkable cities. To develop better urban walking infrastructure, people’s perception is central to the process, and this is why pedestrians may be considered ‘consumers’ of the walking environment. However, existing evaluation tools conduct walking network assessment objectively using spatial data and rarely assesses the ‘perceived’ network attributes. The current research evaluates users’ perception towards ten link and three network attributes using conjoint analysis. A pictorial survey instrument was created for recording users’ responses in two Indian cities. Results shows that, both link and network attributes were perceived to be more important than only link attributes. Respondents preferred ‘accessibility’ and ‘continuity’ over ‘width of sidewalk’ and ‘aesthetics and surface quality’, when presented with both link and network pictorial profiles. This study was able to define two instruments for practitioners—relative importance and tolerance level. Hypothetical ‘products’ could be simulated with high importance and low tolerance attributes and the process shows that a higher preference was seen for ‘products’ with both link and network level improvements.

A comparative analysis of pedestrian network connectivity and accessibility using network approximation

Article

Jul 2023
J TRANSP GEOGR

Modelling perceived pedestrian level of service of sidewalks: a structural equation approach

Article

Full-text available

May 2019
TRANSPORT-VILNIUS

A disparity between developed and developing countries is not only in terms of economy and geography, but also on pedestrians' perceptions and expectations about the level of service of sidewalks. Therefore, it is paramount to find the effect of various built environment measures that impact perceived Pedestrian Level Of Service (PLOS) in context of developing nations. This study investigates the most influential factors of built environment that affect perceived PLOS of sidewalks in Indian context. This is one of the first studies in India that utilize Structural Equation Modelling (SEM) technique to assess pedestrian satisfaction and thereby qualitative PLOS of sidewalks. A total of 502 personal interviews was conducted to extract the pedestrian perception about the quality of sidewalks of Thiruvananthapuram city, a typical Indian city. The results identified four latent exogenous constructs named "Safety", "Security", "Mobility and infrastructure" and "Comfort and convenience" that represent the main aspects of PLOS of sidewalks among which factors of security has exhibited highest loading (λ = 0.60). The study identified that parameters like police patrolling, street lighting, cleaner sidewalks , sidewalk obstructions, sidewalk surface have an evident impact on the level of service of sidewalks. The results of the study provide a significant information for interpreting the aspects of the walking environment that mainly influences the PLOS. This information can help city planners to prepare new strategies, policy interventions that enhance the quality of sidewalks and thus making the city more walkable.

Pedestrian Facilities and Perceived Pedestrian Level of Service (PLOS): A Case Study of Chittagong Metropolitan Area, Bangladesh

Article

Full-text available

Apr 2019

The promotion of active transport (a type of sustainable transportation) such as walking is a form of response against environmental pollution engendering from transport sector. Pedestrian level of service (PLOS) is a measurement tool to evaluate the degree of pedestrian accommodation on roadway to provide a comfortable and safe walking environment. The roadway characteristics-based model to measure PLOS has been widely applied since this approach is conceived as being transferable to different contexts. We present a comprehensive framework to measure the influence of pedestrian facilities on perceived PLOS qualitatively and quantitatively. We modeled triangular relationships among pedestrian facilities, perceived roadway conditions (accessibility, safety, comfort, and attractiveness), and perceived PLOS to identify pedestrian facilities, related to footpath, carriageway, and transit, influencing perceived PLOS. We developed these models for a case study of Chittagong Metropolitan Area in Bangladesh. Poor condition of pedestrian facilities in the region resulted in PLOS B as the highest tier of perceived PLOS. Findings of this study showed that accessibility and attractiveness influenced the perceived PLOS for footpath, carriageway, and transit, whereas safety is an important roadway condition for carriageway and transit facilities. We further measured the influence of 22 selected parameters of pedestrian facilities on roadway conditions and perceived PLOS. We concluded that achieving a better perceived PLOS is dependent on the availability, maintenance, and planning of different pedestrian facilities, as improper placement and poor condition of such facilities increased the probability that a lower level PLOS will be perceived.

Street life and the built environment in an auto-oriented US region

Article

Full-text available

Nov 2018
CITIES

Urban planners and designers believe that the built environment at various geographic scales affects pedestrian activity, but have limited empirical evidence at the street scale, to support their claims. We are just beginning to identify and measure the qualities that generate active street life, and this paper builds on the first few studies to do so. This study measures street design qualities and surrounding urban form variables for 881 block faces in Salt Lake County, Utah, and relates them to pedestrian counts. This is the largest such study to date and includes suburbs as well as cities. At the neighborhood scale, we find that D variables – development density, accessibility to destinations, and distance to transit – are significantly associated with the pedestrian activity. At the street scale, we find significant positive relationships between three urban design qualities – imageability, human scale, and complexity – and pedestrian counts, after controlling for neighborhood-scale variables. Finally, we find that pedestrian counts are positively associated with seven of twenty streetscape features – historic buildings, outdoor dining, buildings with identifiers, less sky view, street furniture, active uses, and accent building colors. This study provides implications for streetscape projects that aim to create walkable places in typical auto-oriented, medium-sized cities.

Pedestrian level of service model for evaluating and improving sidewalks from various land uses

Article

Full-text available

Mar 2018

There are several tools and methods developed for evaluation of sidewalks at street level. But most of the tools have neglected the importance of considering pedestrians' perception in assessing Pedestrian Level of Service (PLOS) of sidewalks. Therefore, in contrast to the earlier research work at the level of service of sidewalks, the present study developed a PLOS model to assess street level sidewalk infrastructure facilities from various land uses considering pedestrians' perceptions. This study specifies 10 sidewalk characteristics that cater various pedestrian needs based on the type of land uses where they belong to. The proposed method has been tested in five Indian cities viz; Delhi, Mumbai, Vadodara, Surat and Ahmedabad. The results of the study indicate that PLOS is capable of identifying the main shortcoming of the street network and sidewalk infrastructure in the form of physical and user characteristics. This method allows pedestrians to convey their needs and expectations to city planners and thus demand for improving existing sidewalks. © 2018 Institute for Transport Studies in the European Economic Integration. All right reserved.

Changes over time in population level transport satisfaction and mode of travel: A 13 year repeat cross-sectional study, UK

Article

Full-text available

Apr 2017

Aim The aim of the study was to examine changes over time in satisfaction with usual transport mode, explore individual and area level characteristics as mediators in the likelihood of transport satisfaction, and whether any changes in transport satisfaction varied by these factors over time. Methods Adults from West Central Scotland, United Kingdom, who participated at both waves of the repeat cross-sectional ‘Transport, Health and Well-being Study’ conducted in 1997 (n=2735) and 2010 (n=2024) were assessed. Individuals completed a detailed postal questionnaire at both time points including self-rated satisfaction with usual transport mode (using a seven point scale subsequently dichotomised to a binary outcome of satisfied (1–2) and other (3–7)). Participants reported usual transport mode for travel to various destinations. A multilevel logistic regression model was used and individuals were nested within areas (c. 4000 population). Results At the 2010 sweep, two thirds (n=1345) of individuals were satisfied with their transport choice. Those with fair/poor health were less satisfied with their usual transport compared to those in better health (Odds Ratio (OR) 0.49, p<0.001). Access to a car was associated with overall transport satisfaction (OR 2.63, p<0.001) and the effect of deprivation on transport satisfaction was mitigated when adjusted by household car access. Transport satisfaction increased more from 1997 to 2010 for retired individuals compared to those in employment (OR 1.40, p=0.032), and for those who travelled by public transport (OR 2.39, p=0.005) and using multiple modes (OR 2.19, p<0.001) compared to those who travelled by car. Conclusions The proportion of those who travelled using public transport, active modes or by multiple mode increased journey satisfaction over time at a greater rate than those who travelled by car, highlighting that continued efforts should be made to promote these more active transport modes which have potential to impact on health.

Service levels of sidewalks for pedestrians under mixed traffic environment using Genetic Programming clustering

Article

Full-text available

Feb 2017

This study aims at developing a model for pedestrian to evaluate service measure at the roadside walking environment from the qualitative and quantitative analysis in developing countries. The potential primary factors influencing service measure of pedestrian were summarized taking consideration to heterogeneous traffic flow condition and perception of road users. Total 735 real-time sense of participant's satisfaction when they are using the sidewalks, road geometric as well as operational characteristics of the road segments were collected from the 73 sites. The selected sites belong to midsized cities with varying geometric features. Different statistical investigations like factor analysis, Wilks’ lambda test and stepwise regression analysis were carried out to develop PLOS model for sidewalk facilities. From the results it has been observed that the variables taken such as width of sidewalk, vehicle volume, pedestrian volume etc. are significantly influencing the pedestrian service measure and the model was validated with a significance value of R2= 0.972. The PLOS scores got from the model are then classified using Genetic Programming clustering to find the six PLOS ranges (A-F) which show score for PLOS A ≤1.8 with best condition and PLOS F > 5.1 having worst condition of service.

Variability in Sidewalk Pedestrian Level of Service Measures and Rating

Article

Dec 2018

Treating walking as a mode, transportation engineers developed the pedestrian level of service (PLOS), a concept evaluating pedestrian traffic characteristics and network capacity, similar to vehicular level of service. Evolution of PLOS resulted in many methods with different scopes and measures trying to better represent the complexity of walking, none of which is superior, nor can their ratings be converted to those of other methods. This paper discusses the variability in PLOS methods proving a lack of consensus and consistency in the literature. A numerical example from the PLOS ratings of 81 walkway locations using 3 different methods shows that each method has benefits, but none of them reflect whole aspects of walking alone. In an attempt to contribute, the need for a revised PLOS rating structure is discussed, suggesting some mathematical techniques to combine different PLOS evaluation results (e.g., minimum value, weighted averaging, and so on). Although this paper defines the main dimensions of walking needed in PLOS evaluations, feedback from different disciplines (e.g., engineering, planning, and psychology) and regions is needed to reach the desired consensus.

Level of service of pedestrian facilities: Modelling human comfort perception in the evaluation of pedestrian behaviour patterns

Article

Oct 2018
TRANSPORT RES F-TRAF

The paper presents a new methodology for evaluating the quality of operation of pedestrian facilities: the methodology is based on the individual level of comfort perceived by each pedestrian that moves in the area. At each time instant, each pedestrian perceives a comfort level which is a function of the space they feel currently available and of his required space. The required space depends on the subject’s walking direction as well as on physical and psychological factors. The available space depends on the current positions of pedestrians. The proposed methodology quantifies the current discomfort due to pedestrian interactions as a continuous function of the interpersonal distances. The proposed methodology has been applied to empirical data. The experimental data are presented, discussed and compared with widely accepted level of service assessment methods.

What Are the Most Important Factors for Pedestrian Level-of-Service Estimation? A Systematic Review of the Literature

Article

Sep 2018

Pedestrian environments are becoming more important in an urbanizing world where walking is increasingly being encouraged. Engineers and planners determine a link’s performance using measures codified as level-of-service, which provide guidance on acceptable or desirable standards. A range of approaches are used in determining pedestrian level-of-service (PLOS), incorporating a wide variety of factors and with much debate as to what should or should not be used. There has been no systematic attempt to synthesize this research and provide an over-arching perspective. Our review surveyed PLOS models from the peer-reviewed literature using a systematic quantitative literature review method based on the protocol developed by the Preferred Reporting Items for Systematic Review Recommendations (PRISMA). PLOS models are increasingly being developed; 22 of the 58 studies surveyed were produced since 2013. Earlier work adapted approaches used to determine automobile LOS to PLOS. Later approaches use a much wider range of factors but with very little consistency across the studies surveyed. Collectively these factors can be grouped in themes of: comfort, safety, and mobility. The most used factors were, in order: footpath width; obstructions to pedestrian flow; motor vehicle speeds and volumes; shoulder widths; and buffers such as on-street parking. However, many of the factors being included have not been empirically studied and almost none of the tools in use have been tested for such matters as inter-rater reliability.

Meta-analysis of the relationships between space syntax measures and pedestrian movement

Article

Aug 2017

Ample research has been conducted investigating the built environment impacts on pedestrian movement (PM). A clear division is also evident in the literature on this topic: one group tends to use geographic measures (metric distance) of the environment to explain pedestrian behaviour; the other group uses syntactic measures (visual distance). Many review articles have been published on the former. However, relatively little is known about the effect size (ES), directions, and consistency of syntactic measures in explaining PM. This paper fills this gap through a meta-analysis of published and unpublished studies on this topic spanning over 1975–2016, and answers the following five research questions: (a) What are the different measures used in the space syntax literature to explain PM?; (b) What are the magnitudes and directions of associations between space syntax measures and PM?; (c) Which space syntax measure has a more consistent relationship with PM?; (d) To what extent do the explanatory powers of different measures vary between their derivation methods?; and (e) What are the likely causes of variations of the reported results in prior studies? This research examined four syntactic measures (integration, connectivity, choice, and control) in a random effect model with 95% confidence interval (CI). The choice and integration measures were further investigated based on their operational approaches (topological, angular and metric). Results show that integration (ES = 0.206, 95% CI = 0.173–0.238, p < 0.001), choice (ES = 0.481, 95% CI = 0.391–0.561, p < 0.001), and connectivity (ES = 0.305, 95% CI = −0.225–0.696, p = 0.257) measures positively influence PM with choice being the strongest predictor. Both connectivity and control (ES = −0.001, 95% CI = −0.117–0.115, p = 0.990) were found to have a statistically insignificant impact. The choice and integration measures show stronger effects when derived using the angular approach (ES = 0.493 for choice, and ES = 0.502 for integration) compared to topological approach (ES = 0.374 for choice, and ES = 0.124 for integration). However, the reported results of all measures are highly heterogeneous, perhaps due to the differences in research design. The significance, magnitude, and consistency of integration and choice measures justify their relevance in built environment interventions to promote PM.

Assessing urban sidewalk networks based on three constructs: a synthesis of pedestrian level of service literature

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